id	sid	tid	token	lemma	pos
alkej-102	1	1	characterization	characterization	NOUN
alkej-102	1	2	of	of	ADP
alkej-102	1	3	delamination	delamination	NOUN
alkej-102	1	4	effect	effect	NOUN
alkej-102	1	5	on	on	ADP
alkej-102	1	6	free	free	ADJ
alkej-102	1	7	vibration	vibration	NOUN
alkej-102	1	8	of	of	ADP
alkej-102	1	9	composite	composite	ADJ
alkej-102	1	10	laminates	laminate	NOUN
alkej-102	1	11	plate	plate	NOUN
alkej-102	1	12	using	use	VERB
alkej-102	1	13	high	high	ADJ
alkej-102	1	14	order	order	NOUN
alkej-102	1	15	shear	shear	NOUN
alkej-102	1	16	deformation	deformation	NOUN
alkej-102	1	17	theory	theory	NOUN
alkej-102	1	18	al	al	PROPN
alkej-102	1	19	-	-	PUNCT
alkej-102	1	20	khwarizmi	khwarizmi	PROPN
alkej-102	1	21	engineering	engineering	PROPN
alkej-102	1	22	journal	journal	PROPN
alkej-102	1	23	al	al	PROPN
alkej-102	1	24	-	-	PUNCT
alkej-102	1	25	khwarizmi	khwarizmi	PROPN
alkej-102	1	26	engineering	engineering	NOUN
alkej-102	1	27	journal	journal	PROPN
alkej-102	1	28	,	,	PUNCT
alkej-102	1	29	vol	vol	NOUN
alkej-102	1	30	.	.	PROPN
alkej-102	1	31	8	8	NUM
alkej-102	1	32	,	,	PUNCT
alkej-102	1	33	no	no	INTJ
alkej-102	1	34	.	.	PUNCT
alkej-102	2	1	1,pp	1,pp	NUM
alkej-102	2	2	18	18	NUM
alkej-102	2	3	-26	-26	SYM
alkej-102	2	4	(	(	PUNCT
alkej-102	2	5	2012	2012	NUM
alkej-102	2	6	)	)	PUNCT
alkej-102	2	7	color	color	NOUN
alkej-102	2	8	image	image	NOUN
alkej-102	2	9	denoising	denoising	NOUN
alkej-102	2	10	using	use	VERB
alkej-102	2	11	stationary	stationary	ADJ
alkej-102	2	12	wavelet	wavelet	NOUN
alkej-102	2	13	transform	transform	NOUN
alkej-102	2	14	and	and	CCONJ
alkej-102	2	15	adaptive	adaptive	ADJ
alkej-102	2	16	wiener	wiener	NOUN
alkej-102	2	17	filter	filter	NOUN
alkej-102	2	18	iman	iman	PROPN
alkej-102	2	19	m.g	m.g	PROPN
alkej-102	2	20	.	.	PROPN
alkej-102	2	21	alwan	alwan	PROPN
alkej-102	2	22	department	department	PROPN
alkej-102	2	23	of	of	ADP
alkej-102	2	24	computer	computer	NOUN
alkej-102	2	25	science	science	NOUN
alkej-102	2	26	/college	/college	PROPN
alkej-102	2	27	of	of	ADP
alkej-102	2	28	education	education	NOUN
alkej-102	2	29	for	for	ADP
alkej-102	2	30	women	woman	NOUN
alkej-102	2	31	/university	/university	PUNCT
alkej-102	2	32	of	of	ADP
alkej-102	2	33	baghdad	baghdad	PROPN
alkej-102	2	34	email	email	NOUN
alkej-102	2	35	:	:	PUNCT
alkej-102	2	36	ainms_66@yahoo.com	ainms_66@yahoo.com	X
alkej-102	2	37	(	(	PUNCT
alkej-102	2	38	received	receive	VERB
alkej-102	2	39	december	december	PROPN
alkej-102	2	40	2011	2011	NUM
alkej-102	2	41	;	;	PUNCT
alkej-102	2	42	accepted	accept	VERB
alkej-102	2	43	january	january	PROPN
alkej-102	2	44	2012	2012	NUM
alkej-102	2	45	)	)	PUNCT
alkej-102	2	46	abstract	abstract	ADP
alkej-102	2	47	the	the	DET
alkej-102	2	48	denoising	denoising	NOUN
alkej-102	2	49	of	of	ADP
alkej-102	2	50	a	a	DET
alkej-102	2	51	natural	natural	ADJ
alkej-102	2	52	image	image	NOUN
alkej-102	2	53	corrupted	corrupt	VERB
alkej-102	2	54	by	by	ADP
alkej-102	2	55	gaussian	gaussian	ADJ
alkej-102	2	56	noise	noise	NOUN
alkej-102	2	57	is	be	AUX
alkej-102	2	58	a	a	DET
alkej-102	2	59	problem	problem	NOUN
alkej-102	2	60	in	in	ADP
alkej-102	2	61	signal	signal	NOUN
alkej-102	2	62	or	or	CCONJ
alkej-102	2	63	image	image	NOUN
alkej-102	2	64	processing	processing	NOUN
alkej-102	2	65	.	.	PUNCT
alkej-102	3	1	much	much	ADJ
alkej-102	3	2	work	work	NOUN
alkej-102	3	3	has	have	AUX
alkej-102	3	4	been	be	AUX
alkej-102	3	5	done	do	VERB
alkej-102	3	6	in	in	ADP
alkej-102	3	7	the	the	DET
alkej-102	3	8	field	field	NOUN
alkej-102	3	9	of	of	ADP
alkej-102	3	10	wavelet	wavelet	NOUN
alkej-102	3	11	thresholding	thresholding	NOUN
alkej-102	3	12	but	but	CCONJ
alkej-102	3	13	most	most	ADJ
alkej-102	3	14	of	of	ADP
alkej-102	3	15	it	it	PRON
alkej-102	3	16	was	be	AUX
alkej-102	3	17	focused	focus	VERB
alkej-102	3	18	on	on	ADP
alkej-102	3	19	statistical	statistical	ADJ
alkej-102	3	20	modeling	modeling	NOUN
alkej-102	3	21	of	of	ADP
alkej-102	3	22	wavelet	wavelet	NOUN
alkej-102	3	23	coefficients	coefficient	NOUN
alkej-102	3	24	and	and	CCONJ
alkej-102	3	25	the	the	DET
alkej-102	3	26	optimal	optimal	ADJ
alkej-102	3	27	choice	choice	NOUN
alkej-102	3	28	of	of	ADP
alkej-102	3	29	thresholds	threshold	NOUN
alkej-102	3	30	.	.	PUNCT
alkej-102	4	1	this	this	DET
alkej-102	4	2	paper	paper	NOUN
alkej-102	4	3	describes	describe	VERB
alkej-102	4	4	a	a	DET
alkej-102	4	5	new	new	ADJ
alkej-102	4	6	method	method	NOUN
alkej-102	4	7	for	for	ADP
alkej-102	4	8	the	the	DET
alkej-102	4	9	suppression	suppression	NOUN
alkej-102	4	10	of	of	ADP
alkej-102	4	11	noise	noise	NOUN
alkej-102	4	12	in	in	ADP
alkej-102	4	13	image	image	NOUN
alkej-102	4	14	by	by	ADP
alkej-102	4	15	fusing	fuse	VERB
alkej-102	4	16	the	the	DET
alkej-102	4	17	stationary	stationary	ADJ
alkej-102	4	18	wavelet	wavelet	NOUN
alkej-102	4	19	denoising	denoising	NOUN
alkej-102	4	20	technique	technique	NOUN
alkej-102	4	21	with	with	ADP
alkej-102	4	22	adaptive	adaptive	ADJ
alkej-102	4	23	wiener	wiener	NOUN
alkej-102	4	24	filter	filter	NOUN
alkej-102	4	25	.	.	PUNCT
alkej-102	5	1	the	the	DET
alkej-102	5	2	wiener	wiener	NOUN
alkej-102	5	3	filter	filter	NOUN
alkej-102	5	4	is	be	AUX
alkej-102	5	5	applied	apply	VERB
alkej-102	5	6	to	to	ADP
alkej-102	5	7	the	the	DET
alkej-102	5	8	reconstructed	reconstructed	ADJ
alkej-102	5	9	image	image	NOUN
alkej-102	5	10	for	for	ADP
alkej-102	5	11	the	the	DET
alkej-102	5	12	approximation	approximation	NOUN
alkej-102	5	13	coefficients	coefficient	NOUN
alkej-102	5	14	only	only	ADV
alkej-102	5	15	,	,	PUNCT
alkej-102	5	16	while	while	SCONJ
alkej-102	5	17	the	the	DET
alkej-102	5	18	thresholding	thresholding	NOUN
alkej-102	5	19	technique	technique	NOUN
alkej-102	5	20	is	be	AUX
alkej-102	5	21	applied	apply	VERB
alkej-102	5	22	to	to	ADP
alkej-102	5	23	the	the	DET
alkej-102	5	24	details	detail	NOUN
alkej-102	5	25	coefficients	coefficient	NOUN
alkej-102	5	26	of	of	ADP
alkej-102	5	27	the	the	DET
alkej-102	5	28	transform	transform	NOUN
alkej-102	5	29	,	,	PUNCT
alkej-102	5	30	then	then	ADV
alkej-102	5	31	get	get	VERB
alkej-102	5	32	the	the	DET
alkej-102	5	33	final	final	ADJ
alkej-102	5	34	denoised	denoise	VERB
alkej-102	5	35	image	image	NOUN
alkej-102	5	36	is	be	AUX
alkej-102	5	37	obtained	obtain	VERB
alkej-102	5	38	by	by	ADP
alkej-102	5	39	combining	combine	VERB
alkej-102	5	40	the	the	DET
alkej-102	5	41	two	two	NUM
alkej-102	5	42	results	result	NOUN
alkej-102	5	43	.	.	PUNCT
alkej-102	6	1	the	the	DET
alkej-102	6	2	proposed	propose	VERB
alkej-102	6	3	method	method	NOUN
alkej-102	6	4	was	be	AUX
alkej-102	6	5	applied	apply	VERB
alkej-102	6	6	by	by	ADP
alkej-102	6	7	using	use	VERB
alkej-102	6	8	matlab	matlab	PROPN
alkej-102	6	9	r2010a	r2010a	PROPN
alkej-102	6	10	with	with	ADP
alkej-102	6	11	color	color	NOUN
alkej-102	6	12	images	image	NOUN
alkej-102	6	13	contaminated	contaminate	VERB
alkej-102	6	14	by	by	ADP
alkej-102	6	15	white	white	ADJ
alkej-102	6	16	gaussian	gaussian	PROPN
alkej-102	6	17	noise	noise	NOUN
alkej-102	6	18	.	.	PUNCT
alkej-102	7	1	compared	compare	VERB
alkej-102	7	2	with	with	ADP
alkej-102	7	3	stationary	stationary	ADJ
alkej-102	7	4	wavelet	wavelet	NOUN
alkej-102	7	5	and	and	CCONJ
alkej-102	7	6	wiener	wiener	NOUN
alkej-102	7	7	filter	filter	NOUN
alkej-102	7	8	algorithms	algorithm	NOUN
alkej-102	7	9	,	,	PUNCT
alkej-102	7	10	the	the	DET
alkej-102	7	11	experimental	experimental	ADJ
alkej-102	7	12	results	result	NOUN
alkej-102	7	13	show	show	VERB
alkej-102	7	14	that	that	SCONJ
alkej-102	7	15	the	the	DET
alkej-102	7	16	proposed	propose	VERB
alkej-102	7	17	method	method	NOUN
alkej-102	7	18	provides	provide	VERB
alkej-102	7	19	better	well	ADJ
alkej-102	7	20	subjective	subjective	ADJ
alkej-102	7	21	and	and	CCONJ
alkej-102	7	22	objective	objective	ADJ
alkej-102	7	23	quality	quality	NOUN
alkej-102	7	24	,	,	PUNCT
alkej-102	7	25	and	and	CCONJ
alkej-102	7	26	obtain	obtain	VERB
alkej-102	7	27	up	up	ADP
alkej-102	7	28	to	to	PART
alkej-102	7	29	3.5	3.5	NUM
alkej-102	7	30	db	db	NOUN
alkej-102	7	31	psnr	psnr	NOUN
alkej-102	7	32	improvement	improvement	NOUN
alkej-102	7	33	.	.	PUNCT
alkej-102	8	1	keywords	keyword	NOUN
alkej-102	8	2	:	:	PUNCT
alkej-102	8	3	stationary	stationary	ADJ
alkej-102	8	4	wavelet	wavelet	NOUN
alkej-102	8	5	transform	transform	NOUN
alkej-102	8	6	(	(	PUNCT
alkej-102	8	7	swt	swt	PROPN
alkej-102	8	8	)	)	PUNCT
alkej-102	8	9	,	,	PUNCT
alkej-102	8	10	adaptive	adaptive	ADJ
alkej-102	8	11	wiener	wiener	NOUN
alkej-102	8	12	filter	filter	NOUN
alkej-102	8	13	,	,	PUNCT
alkej-102	8	14	thresholding	thresholde	VERB
alkej-102	8	15	.	.	PUNCT
alkej-102	9	1	1	1	X
alkej-102	9	2	.	.	X
alkej-102	9	3	introduction	introduction	NOUN
alkej-102	9	4	images	image	NOUN
alkej-102	9	5	acquired	acquire	VERB
alkej-102	9	6	through	through	ADP
alkej-102	9	7	sensors	sensor	NOUN
alkej-102	9	8	[	[	X
alkej-102	9	9	chargecoupled	chargecoupled	ADJ
alkej-102	9	10	device	device	NOUN
alkej-102	9	11	(	(	PUNCT
alkej-102	9	12	ccd	ccd	NOUN
alkej-102	9	13	)	)	PUNCT
alkej-102	9	14	]	]	PUNCT
alkej-102	9	15	cameras	camera	NOUN
alkej-102	9	16	may	may	AUX
alkej-102	9	17	be	be	AUX
alkej-102	9	18	contaminated	contaminate	VERB
alkej-102	9	19	by	by	ADP
alkej-102	9	20	noise	noise	NOUN
alkej-102	9	21	sources	source	NOUN
alkej-102	9	22	.	.	PUNCT
alkej-102	10	1	image	image	NOUN
alkej-102	10	2	processing	processing	NOUN
alkej-102	10	3	technique	technique	NOUN
alkej-102	10	4	also	also	ADV
alkej-102	10	5	corrupts	corrupt	VERB
alkej-102	10	6	image	image	NOUN
alkej-102	10	7	with	with	ADP
alkej-102	10	8	noise	noise	NOUN
alkej-102	10	9	,	,	PUNCT
alkej-102	10	10	leading	lead	VERB
alkej-102	10	11	to	to	ADP
alkej-102	10	12	significant	significant	ADJ
alkej-102	10	13	reduction	reduction	NOUN
alkej-102	10	14	in	in	ADP
alkej-102	10	15	quality	quality	NOUN
alkej-102	10	16	.	.	PUNCT
alkej-102	11	1	traditionally	traditionally	ADV
alkej-102	11	2	,	,	PUNCT
alkej-102	11	3	linear	linear	ADJ
alkej-102	11	4	filters	filter	NOUN
alkej-102	11	5	(	(	PUNCT
alkej-102	11	6	mean	mean	ADJ
alkej-102	11	7	,	,	PUNCT
alkej-102	11	8	median	median	ADJ
alkej-102	11	9	,	,	PUNCT
alkej-102	11	10	and	and	CCONJ
alkej-102	11	11	wiener	wiener	NOUN
alkej-102	11	12	filter	filter	NOUN
alkej-102	11	13	)	)	PUNCT
alkej-102	11	14	are	be	AUX
alkej-102	11	15	used	use	VERB
alkej-102	11	16	for	for	ADP
alkej-102	11	17	removing	remove	VERB
alkej-102	11	18	noise	noise	NOUN
alkej-102	11	19	from	from	ADP
alkej-102	11	20	images	image	NOUN
alkej-102	11	21	,	,	PUNCT
alkej-102	11	22	but	but	CCONJ
alkej-102	11	23	it	it	PRON
alkej-102	11	24	blurs	blur	VERB
alkej-102	11	25	data	datum	NOUN
alkej-102	11	26	[	[	X
alkej-102	11	27	1	1	NUM
alkej-102	11	28	]	]	PUNCT
alkej-102	11	29	.	.	PUNCT
alkej-102	12	1	it	it	PRON
alkej-102	12	2	is	be	AUX
alkej-102	12	3	well	well	ADV
alkej-102	12	4	known	know	VERB
alkej-102	12	5	that	that	SCONJ
alkej-102	12	6	wavelet	wavelet	NOUN
alkej-102	12	7	transform	transform	NOUN
alkej-102	12	8	is	be	AUX
alkej-102	12	9	a	a	DET
alkej-102	12	10	signal	signal	ADJ
alkej-102	12	11	processing	processing	NOUN
alkej-102	12	12	technique	technique	NOUN
alkej-102	12	13	which	which	PRON
alkej-102	12	14	can	can	AUX
alkej-102	12	15	display	display	VERB
alkej-102	12	16	the	the	DET
alkej-102	12	17	signals	signal	NOUN
alkej-102	12	18	on	on	ADP
alkej-102	12	19	in	in	ADP
alkej-102	12	20	both	both	DET
alkej-102	12	21	time	time	NOUN
alkej-102	12	22	and	and	CCONJ
alkej-102	12	23	frequency	frequency	NOUN
alkej-102	12	24	domain	domain	NOUN
alkej-102	12	25	.	.	PUNCT
alkej-102	13	1	wavelet	wavelet	NOUN
alkej-102	13	2	transform	transform	NOUN
alkej-102	13	3	is	be	AUX
alkej-102	13	4	superior	superior	ADJ
alkej-102	13	5	approach	approach	NOUN
alkej-102	13	6	to	to	ADP
alkej-102	13	7	other	other	ADJ
alkej-102	13	8	time	time	NOUN
alkej-102	13	9	-	-	PUNCT
alkej-102	13	10	frequency	frequency	NOUN
alkej-102	13	11	analysis	analysis	NOUN
alkej-102	13	12	tools	tool	NOUN
alkej-102	13	13	because	because	SCONJ
alkej-102	13	14	its	its	PRON
alkej-102	13	15	time	time	NOUN
alkej-102	13	16	scale	scale	NOUN
alkej-102	13	17	width	width	NOUN
alkej-102	13	18	of	of	ADP
alkej-102	13	19	the	the	DET
alkej-102	13	20	window	window	NOUN
alkej-102	13	21	can	can	AUX
alkej-102	13	22	be	be	AUX
alkej-102	13	23	stretched	stretch	VERB
alkej-102	13	24	to	to	PART
alkej-102	13	25	match	match	VERB
alkej-102	13	26	the	the	DET
alkej-102	13	27	original	original	ADJ
alkej-102	13	28	signal	signal	NOUN
alkej-102	13	29	,	,	PUNCT
alkej-102	13	30	especially	especially	ADV
alkej-102	13	31	in	in	ADP
alkej-102	13	32	image	image	NOUN
alkej-102	13	33	processing	processing	NOUN
alkej-102	13	34	studies	study	NOUN
alkej-102	13	35	.	.	PUNCT
alkej-102	14	1	this	this	PRON
alkej-102	14	2	makes	make	VERB
alkej-102	14	3	it	it	PRON
alkej-102	14	4	particularly	particularly	ADV
alkej-102	14	5	useful	useful	ADJ
alkej-102	14	6	for	for	ADP
alkej-102	14	7	nonstationary	nonstationary	ADJ
alkej-102	14	8	signal	signal	NOUN
alkej-102	14	9	analysis	analysis	NOUN
alkej-102	14	10	,	,	PUNCT
alkej-102	14	11	such	such	ADJ
alkej-102	14	12	as	as	ADP
alkej-102	14	13	noises	noise	NOUN
alkej-102	14	14	and	and	CCONJ
alkej-102	14	15	transients	transient	NOUN
alkej-102	14	16	.	.	PUNCT
alkej-102	15	1	for	for	ADP
alkej-102	15	2	a	a	DET
alkej-102	15	3	discrete	discrete	ADJ
alkej-102	15	4	signal	signal	NOUN
alkej-102	15	5	,	,	PUNCT
alkej-102	15	6	a	a	DET
alkej-102	15	7	fast	fast	ADJ
alkej-102	15	8	algorithm	algorithm	NOUN
alkej-102	15	9	of	of	ADP
alkej-102	15	10	discrete	discrete	ADJ
alkej-102	15	11	wavelet	wavelet	NOUN
alkej-102	15	12	transform	transform	NOUN
alkej-102	15	13	(	(	PUNCT
alkej-102	15	14	dwt	dwt	NOUN
alkej-102	15	15	)	)	PUNCT
alkej-102	15	16	is	be	AUX
alkej-102	15	17	multiresolution	multiresolution	NOUN
alkej-102	15	18	analysis	analysis	NOUN
alkej-102	15	19	,	,	PUNCT
alkej-102	15	20	which	which	PRON
alkej-102	15	21	is	be	AUX
alkej-102	15	22	a	a	DET
alkej-102	15	23	nonredundant	nonredundant	ADJ
alkej-102	15	24	decomposition	decomposition	NOUN
alkej-102	16	1	[	[	X
alkej-102	16	2	2	2	NUM
alkej-102	16	3	]	]	PUNCT
alkej-102	16	4	.	.	PUNCT
alkej-102	17	1	one	one	NUM
alkej-102	17	2	of	of	ADP
alkej-102	17	3	the	the	DET
alkej-102	17	4	most	most	ADV
alkej-102	17	5	popular	popular	ADJ
alkej-102	17	6	method	method	NOUN
alkej-102	17	7	consists	consist	VERB
alkej-102	17	8	of	of	ADP
alkej-102	17	9	thresholding	thresholde	VERB
alkej-102	17	10	the	the	DET
alkej-102	17	11	wavelet	wavelet	NOUN
alkej-102	17	12	coefficients	coefficient	NOUN
alkej-102	17	13	(	(	PUNCT
alkej-102	17	14	using	use	VERB
alkej-102	17	15	hard	hard	ADJ
alkej-102	17	16	threshold	threshold	NOUN
alkej-102	17	17	or	or	CCONJ
alkej-102	17	18	the	the	DET
alkej-102	17	19	soft	soft	ADJ
alkej-102	17	20	threshold	threshold	NOUN
alkej-102	17	21	)	)	PUNCT
alkej-102	17	22	as	as	SCONJ
alkej-102	17	23	introduced	introduce	VERB
alkej-102	17	24	by	by	ADP
alkej-102	17	25	donoho	donoho	NOUN
alkej-102	17	26	[	[	X
alkej-102	17	27	3	3	NUM
alkej-102	17	28	]	]	PUNCT
alkej-102	17	29	.	.	PUNCT
alkej-102	18	1	elyasi	elyasi	NOUN
alkej-102	18	2	and	and	CCONJ
alkej-102	18	3	zarmehi	zarmehi	NOUN
alkej-102	19	1	[	[	X
alkej-102	19	2	4	4	NUM
alkej-102	19	3	]	]	PUNCT
alkej-102	19	4	proposed	propose	VERB
alkej-102	19	5	several	several	ADJ
alkej-102	19	6	methods	method	NOUN
alkej-102	19	7	of	of	ADP
alkej-102	19	8	noise	noise	NOUN
alkej-102	19	9	removal	removal	NOUN
alkej-102	19	10	from	from	ADP
alkej-102	19	11	degraded	degraded	ADJ
alkej-102	19	12	images	image	NOUN
alkej-102	19	13	with	with	ADP
alkej-102	19	14	gaussian	gaussian	ADJ
alkej-102	19	15	noise	noise	NOUN
alkej-102	19	16	by	by	ADP
alkej-102	19	17	using	use	VERB
alkej-102	19	18	adaptive	adaptive	ADJ
alkej-102	19	19	wavelet	wavelet	NOUN
alkej-102	19	20	threshold	threshold	NOUN
alkej-102	19	21	(	(	PUNCT
alkej-102	19	22	bayes	bayes	NOUN
alkej-102	19	23	shrink	shrink	VERB
alkej-102	19	24	,	,	PUNCT
alkej-102	19	25	modified	modify	VERB
alkej-102	19	26	bayes	bayes	NOUN
alkej-102	19	27	shrink	shrink	NOUN
alkej-102	19	28	and	and	CCONJ
alkej-102	19	29	normal	normal	ADJ
alkej-102	19	30	shrink	shrink	NOUN
alkej-102	19	31	)	)	PUNCT
alkej-102	19	32	.	.	PUNCT
alkej-102	20	1	jacob	jacob	PROPN
alkej-102	20	2	and	and	CCONJ
alkej-102	20	3	martin	martin	PROPN
alkej-102	20	4	[	[	X
alkej-102	20	5	5	5	NUM
alkej-102	20	6	]	]	PUNCT
alkej-102	20	7	performed	perform	VERB
alkej-102	20	8	wiener	wiener	NOUN
alkej-102	20	9	filtering	filtering	NOUN
alkej-102	20	10	on	on	ADP
alkej-102	20	11	the	the	DET
alkej-102	20	12	wavelet	wavelet	NOUN
alkej-102	20	13	coefficients	coefficient	NOUN
alkej-102	20	14	to	to	PART
alkej-102	20	15	denoise	denoise	VERB
alkej-102	20	16	an	an	DET
alkej-102	20	17	image	image	NOUN
alkej-102	20	18	degraded	degrade	VERB
alkej-102	20	19	by	by	ADP
alkej-102	20	20	an	an	DET
alkej-102	20	21	additive	additive	ADJ
alkej-102	20	22	white	white	ADJ
alkej-102	20	23	gaussian	gaussian	NOUN
alkej-102	20	24	noise	noise	NOUN
alkej-102	20	25	(	(	PUNCT
alkej-102	20	26	awgn	awgn	NOUN
alkej-102	20	27	)	)	PUNCT
alkej-102	20	28	.	.	PUNCT
alkej-102	21	1	jin	jin	PROPN
alkej-102	21	2	et	et	PROPN
alkej-102	21	3	.	.	PUNCT
alkej-102	22	1	al	al	PROPN
alkej-102	22	2	.	.	PUNCT
alkej-102	23	1	[	[	X
alkej-102	23	2	6	6	NUM
alkej-102	23	3	]	]	PUNCT
alkej-102	23	4	considered	consider	VERB
alkej-102	23	5	the	the	DET
alkej-102	23	6	adaptive	adaptive	ADJ
alkej-102	23	7	wiener	wiener	NOUN
alkej-102	23	8	filtering	filtering	NOUN
alkej-102	23	9	of	of	ADP
alkej-102	23	10	noisy	noisy	ADJ
alkej-102	23	11	images	image	NOUN
alkej-102	23	12	and	and	CCONJ
alkej-102	23	13	image	image	NOUN
alkej-102	23	14	sequences	sequence	NOUN
alkej-102	23	15	.	.	PUNCT
alkej-102	24	1	they	they	PRON
alkej-102	24	2	began	begin	VERB
alkej-102	24	3	by	by	ADP
alkej-102	24	4	using	use	VERB
alkej-102	24	5	an	an	DET
alkej-102	24	6	adaptive	adaptive	ADJ
alkej-102	24	7	weighted	weight	VERB
alkej-102	24	8	averaging	averaging	NOUN
alkej-102	24	9	(	(	PUNCT
alkej-102	24	10	awa	awa	PROPN
alkej-102	24	11	)	)	PUNCT
alkej-102	24	12	approach	approach	NOUN
alkej-102	24	13	to	to	PART
alkej-102	24	14	estimate	estimate	VERB
alkej-102	24	15	the	the	DET
alkej-102	24	16	secondorder	secondorder	ADJ
alkej-102	24	17	statistics	statistic	NOUN
alkej-102	24	18	required	require	VERB
alkej-102	24	19	by	by	ADP
alkej-102	24	20	the	the	DET
alkej-102	24	21	wiener	wiener	NOUN
alkej-102	24	22	filter	filter	NOUN
alkej-102	24	23	and	and	CCONJ
alkej-102	24	24	extended	extend	VERB
alkej-102	24	25	the	the	DET
alkej-102	24	26	awa	awa	PROPN
alkej-102	24	27	concept	concept	NOUN
alkej-102	24	28	to	to	ADP
alkej-102	24	29	the	the	DET
alkej-102	24	30	wavelet	wavelet	NOUN
alkej-102	24	31	domain	domain	NOUN
alkej-102	24	32	and	and	CCONJ
alkej-102	24	33	that	that	PRON
alkej-102	24	34	gained	gain	VERB
alkej-102	24	35	0.5	0.5	NUM
alkej-102	24	36	db	db	NOUN
alkej-102	24	37	over	over	ADP
alkej-102	24	38	traditional	traditional	ADJ
alkej-102	24	39	wavelet	wavelet	NOUN
alkej-102	24	40	wiener	wiener	NOUN
alkej-102	24	41	filter	filter	NOUN
alkej-102	24	42	.	.	PUNCT
alkej-102	25	1	the	the	DET
alkej-102	25	2	drawback	drawback	NOUN
alkej-102	25	3	of	of	ADP
alkej-102	25	4	nonredundant	nonredundant	ADJ
alkej-102	25	5	transform	transform	NOUN
alkej-102	25	6	is	be	AUX
alkej-102	25	7	their	their	PRON
alkej-102	25	8	noninvariance	noninvariance	NOUN
alkej-102	25	9	in	in	ADP
alkej-102	25	10	time	time	NOUN
alkej-102	25	11	/	/	SYM
alkej-102	25	12	space	space	NOUN
alkej-102	25	13	;	;	PUNCT
alkej-102	25	14	i.e.	i.e.	X
alkej-102	25	15	,	,	PUNCT
alkej-102	25	16	the	the	DET
alkej-102	25	17	coefficients	coefficient	NOUN
alkej-102	25	18	of	of	ADP
alkej-102	25	19	a	a	DET
alkej-102	25	20	delayed	delay	VERB
alkej-102	25	21	signal	signal	NOUN
alkej-102	25	22	are	be	AUX
alkej-102	25	23	not	not	PART
alkej-102	25	24	a	a	DET
alkej-102	25	25	timeshifted	timeshifte	VERB
alkej-102	25	26	version	version	NOUN
alkej-102	25	27	those	those	PRON
alkej-102	25	28	of	of	ADP
alkej-102	25	29	the	the	DET
alkej-102	25	30	original	original	ADJ
alkej-102	25	31	signal	signal	NOUN
alkej-102	25	32	.	.	PUNCT
alkej-102	26	1	the	the	DET
alkej-102	26	2	stationary	stationary	ADJ
alkej-102	26	3	wavelet	wavelet	NOUN
alkej-102	26	4	transform	transform	NOUN
alkej-102	26	5	(	(	PUNCT
alkej-102	26	6	swt	swt	PROPN
alkej-102	26	7	)	)	PUNCT
alkej-102	26	8	was	be	AUX
alkej-102	26	9	introduced	introduce	VERB
alkej-102	26	10	in	in	ADP
alkej-102	26	11	1996	1996	NUM
alkej-102	26	12	to	to	PART
alkej-102	26	13	make	make	VERB
alkej-102	26	14	the	the	DET
alkej-102	26	15	wavelet	wavelet	NOUN
alkej-102	26	16	decomposition	decomposition	NOUN
alkej-102	26	17	time	time	NOUN
alkej-102	26	18	invariant	invariant	ADJ
alkej-102	26	19	[	[	X
alkej-102	26	20	7	7	NUM
alkej-102	26	21	]	]	PUNCT
alkej-102	26	22	.	.	PUNCT
alkej-102	27	1	this	this	PRON
alkej-102	27	2	improves	improve	VERB
alkej-102	27	3	mailto:ainms_66@yahoo.com	mailto:ainms_66@yahoo.com	PROPN
alkej-102	27	4	iman	iman	PROPN
alkej-102	27	5	m.g	m.g	PROPN
alkej-102	27	6	.	.	PROPN
alkej-102	27	7	alwan	alwan	PROPN
alkej-102	27	8	al	al	PROPN
alkej-102	27	9	-	-	PUNCT
alkej-102	27	10	khwarizmi	khwarizmi	PROPN
alkej-102	27	11	engineering	engineering	NOUN
alkej-102	27	12	journal	journal	PROPN
alkej-102	27	13	,	,	PUNCT
alkej-102	27	14	vol	vol	NOUN
alkej-102	27	15	.	.	PROPN
alkej-102	27	16	8	8	NUM
alkej-102	27	17	,	,	PUNCT
alkej-102	27	18	no	no	INTJ
alkej-102	27	19	.	.	PUNCT
alkej-102	28	1	1,pp	1,pp	NUM
alkej-102	28	2	18	18	NUM
alkej-102	28	3	26	26	NUM
alkej-102	28	4	(	(	PUNCT
alkej-102	28	5	2012	2012	NUM
alkej-102	28	6	)	)	PUNCT
alkej-102	28	7	19	19	NUM
alkej-102	28	8	the	the	DET
alkej-102	28	9	power	power	NOUN
alkej-102	28	10	of	of	ADP
alkej-102	28	11	wavelet	wavelet	NOUN
alkej-102	28	12	in	in	ADP
alkej-102	28	13	signal	signal	NOUN
alkej-102	28	14	de	de	X
alkej-102	28	15	-	-	NOUN
alkej-102	28	16	noising	noising	NOUN
alkej-102	28	17	.	.	PUNCT
alkej-102	29	1	this	this	DET
alkej-102	29	2	paper	paper	NOUN
alkej-102	29	3	exploits	exploit	VERB
alkej-102	29	4	the	the	DET
alkej-102	29	5	benefits	benefit	NOUN
alkej-102	29	6	of	of	ADP
alkej-102	29	7	stationary	stationary	ADJ
alkej-102	29	8	wavelet	wavelet	NOUN
alkej-102	29	9	transform	transform	NOUN
alkej-102	29	10	in	in	ADP
alkej-102	29	11	suppressing	suppress	VERB
alkej-102	29	12	noise	noise	NOUN
alkej-102	29	13	at	at	ADP
alkej-102	29	14	high	high	ADJ
alkej-102	29	15	frequencies	frequency	NOUN
alkej-102	29	16	and	and	CCONJ
alkej-102	29	17	wiener	wiener	NOUN
alkej-102	29	18	filter	filter	NOUN
alkej-102	29	19	to	to	PART
alkej-102	29	20	suppress	suppress	VERB
alkej-102	29	21	noise	noise	NOUN
alkej-102	29	22	in	in	ADP
alkej-102	29	23	low	low	ADJ
alkej-102	29	24	frequency	frequency	NOUN
alkej-102	29	25	bands	band	NOUN
alkej-102	29	26	.	.	PUNCT
alkej-102	30	1	the	the	DET
alkej-102	30	2	proposed	propose	VERB
alkej-102	30	3	algorithm	algorithm	NOUN
alkej-102	30	4	is	be	AUX
alkej-102	30	5	divided	divide	VERB
alkej-102	30	6	into	into	ADP
alkej-102	30	7	two	two	NUM
alkej-102	30	8	steps	step	NOUN
alkej-102	30	9	.	.	PUNCT
alkej-102	31	1	after	after	ADP
alkej-102	31	2	taking	take	VERB
alkej-102	31	3	swt	swt	PROPN
alkej-102	31	4	to	to	ADP
alkej-102	31	5	the	the	DET
alkej-102	31	6	noisy	noisy	ADJ
alkej-102	31	7	image	image	NOUN
alkej-102	31	8	,	,	PUNCT
alkej-102	31	9	soft	soft	ADJ
alkej-102	31	10	thresholding	thresholding	NOUN
alkej-102	31	11	method	method	NOUN
alkej-102	31	12	is	be	AUX
alkej-102	31	13	applied	apply	VERB
alkej-102	31	14	to	to	ADP
alkej-102	31	15	the	the	DET
alkej-102	31	16	details	detail	NOUN
alkej-102	31	17	subbands	subband	NOUN
alkej-102	31	18	;	;	PUNCT
alkej-102	31	19	then	then	ADV
alkej-102	31	20	a	a	DET
alkej-102	31	21	transformed	transform	VERB
alkej-102	31	22	image	image	NOUN
alkej-102	31	23	is	be	AUX
alkej-102	31	24	generated	generate	VERB
alkej-102	31	25	from	from	ADP
alkej-102	31	26	approximation	approximation	NOUN
alkej-102	31	27	subband	subband	NOUN
alkej-102	31	28	only	only	ADV
alkej-102	31	29	while	while	SCONJ
alkej-102	31	30	the	the	DET
alkej-102	31	31	other	other	ADJ
alkej-102	31	32	subbands	subband	NOUN
alkej-102	31	33	are	be	AUX
alkej-102	31	34	made	make	VERB
alkej-102	31	35	equal	equal	ADJ
alkej-102	31	36	to	to	ADP
alkej-102	31	37	zero	zero	NUM
alkej-102	31	38	,	,	PUNCT
alkej-102	31	39	applying	apply	VERB
alkej-102	31	40	inverse	inverse	NOUN
alkej-102	31	41	swt	swt	PROPN
alkej-102	31	42	to	to	ADP
alkej-102	31	43	the	the	DET
alkej-102	31	44	generated	generate	VERB
alkej-102	31	45	2	2	NUM
alkej-102	31	46	-	-	PUNCT
alkej-102	31	47	d	d	NOUN
alkej-102	31	48	array	array	NOUN
alkej-102	31	49	,	,	PUNCT
alkej-102	31	50	then	then	ADV
alkej-102	31	51	applying	apply	VERB
alkej-102	31	52	the	the	DET
alkej-102	31	53	adaptive	adaptive	ADJ
alkej-102	31	54	wiener	wiener	NOUN
alkej-102	31	55	filter	filter	NOUN
alkej-102	31	56	,	,	PUNCT
alkej-102	31	57	to	to	PART
alkej-102	31	58	remove	remove	VERB
alkej-102	31	59	the	the	DET
alkej-102	31	60	residual	residual	ADJ
alkej-102	31	61	noise	noise	NOUN
alkej-102	31	62	in	in	ADP
alkej-102	31	63	the	the	DET
alkej-102	31	64	low	low	ADJ
alkej-102	31	65	frequency	frequency	NOUN
alkej-102	31	66	band	band	NOUN
alkej-102	31	67	.	.	PUNCT
alkej-102	32	1	after	after	ADP
alkej-102	32	2	that	that	PRON
alkej-102	32	3	the	the	DET
alkej-102	32	4	approximation	approximation	NOUN
alkej-102	32	5	band	band	NOUN
alkej-102	32	6	is	be	AUX
alkej-102	32	7	returned	return	VERB
alkej-102	32	8	by	by	ADP
alkej-102	32	9	applying	apply	VERB
alkej-102	32	10	swt	swt	PROPN
alkej-102	32	11	to	to	ADP
alkej-102	32	12	the	the	DET
alkej-102	32	13	denoised	denoise	VERB
alkej-102	32	14	signal	signal	NOUN
alkej-102	32	15	,	,	PUNCT
alkej-102	32	16	the	the	DET
alkej-102	32	17	resulted	resulted	ADJ
alkej-102	32	18	approximation	approximation	NOUN
alkej-102	32	19	subband	subband	NOUN
alkej-102	32	20	is	be	AUX
alkej-102	32	21	grouped	group	VERB
alkej-102	32	22	with	with	ADP
alkej-102	32	23	the	the	DET
alkej-102	32	24	thresholded	thresholde	VERB
alkej-102	32	25	subbands	subband	NOUN
alkej-102	32	26	,	,	PUNCT
alkej-102	32	27	applying	apply	VERB
alkej-102	32	28	inverse	inverse	NOUN
alkej-102	32	29	swt	swt	PROPN
alkej-102	32	30	to	to	PART
alkej-102	32	31	obtain	obtain	VERB
alkej-102	32	32	the	the	DET
alkej-102	32	33	denoised	denoise	VERB
alkej-102	32	34	image	image	NOUN
alkej-102	32	35	.	.	PUNCT
alkej-102	33	1	the	the	DET
alkej-102	33	2	proposed	propose	VERB
alkej-102	33	3	method	method	NOUN
alkej-102	33	4	is	be	AUX
alkej-102	33	5	compared	compare	VERB
alkej-102	33	6	with	with	ADP
alkej-102	33	7	the	the	DET
alkej-102	33	8	other	other	ADJ
alkej-102	33	9	two	two	NUM
alkej-102	33	10	traditional	traditional	ADJ
alkej-102	33	11	denoising	denoising	NOUN
alkej-102	33	12	methods	method	NOUN
alkej-102	33	13	,	,	PUNCT
alkej-102	33	14	namely	namely	ADV
alkej-102	33	15	swt	swt	PROPN
alkej-102	33	16	and	and	CCONJ
alkej-102	33	17	wiener	wiener	NOUN
alkej-102	33	18	filter	filter	NOUN
alkej-102	33	19	,	,	PUNCT
alkej-102	33	20	to	to	PART
alkej-102	33	21	validate	validate	VERB
alkej-102	33	22	the	the	DET
alkej-102	33	23	denoised	denoise	VERB
alkej-102	33	24	characteristics	characteristic	NOUN
alkej-102	33	25	of	of	ADP
alkej-102	33	26	this	this	DET
alkej-102	33	27	method	method	NOUN
alkej-102	33	28	.	.	PUNCT
alkej-102	34	1	2	2	X
alkej-102	34	2	.	.	X
alkej-102	34	3	stationary	stationary	ADJ
alkej-102	34	4	wavelet	wavelet	NOUN
alkej-102	34	5	method	method	NOUN
alkej-102	34	6	this	this	DET
alkej-102	34	7	section	section	NOUN
alkej-102	34	8	presents	present	VERB
alkej-102	34	9	the	the	DET
alkej-102	34	10	basic	basic	ADJ
alkej-102	34	11	principals	principal	NOUN
alkej-102	34	12	of	of	ADP
alkej-102	34	13	the	the	DET
alkej-102	34	14	swt	swt	PROPN
alkej-102	34	15	method	method	NOUN
alkej-102	34	16	.	.	PUNCT
alkej-102	35	1	in	in	ADP
alkej-102	35	2	summary	summary	NOUN
alkej-102	35	3	,	,	PUNCT
alkej-102	35	4	the	the	DET
alkej-102	35	5	swt	swt	PROPN
alkej-102	35	6	method	method	NOUN
alkej-102	35	7	can	can	AUX
alkej-102	35	8	be	be	AUX
alkej-102	35	9	described	describe	VERB
alkej-102	35	10	as	as	ADP
alkej-102	35	11	follows	follow	VERB
alkej-102	35	12	.	.	PUNCT
alkej-102	36	1	at	at	ADP
alkej-102	36	2	each	each	DET
alkej-102	36	3	level	level	NOUN
alkej-102	36	4	,	,	PUNCT
alkej-102	36	5	when	when	SCONJ
alkej-102	36	6	the	the	DET
alkej-102	36	7	high	high	ADJ
alkej-102	36	8	-	-	PUNCT
alkej-102	36	9	pass	pass	NOUN
alkej-102	36	10	and	and	CCONJ
alkej-102	36	11	low	low	ADJ
alkej-102	36	12	-	-	PUNCT
alkej-102	36	13	pass	pass	NOUN
alkej-102	36	14	filters	filter	NOUN
alkej-102	36	15	are	be	AUX
alkej-102	36	16	applied	apply	VERB
alkej-102	36	17	to	to	ADP
alkej-102	36	18	the	the	DET
alkej-102	36	19	data	datum	NOUN
alkej-102	36	20	,	,	PUNCT
alkej-102	36	21	the	the	DET
alkej-102	36	22	two	two	NUM
alkej-102	36	23	new	new	ADJ
alkej-102	36	24	sequences	sequence	NOUN
alkej-102	36	25	have	have	VERB
alkej-102	36	26	the	the	DET
alkej-102	36	27	same	same	ADJ
alkej-102	36	28	length	length	NOUN
alkej-102	36	29	as	as	ADP
alkej-102	36	30	the	the	DET
alkej-102	36	31	original	original	ADJ
alkej-102	36	32	sequences	sequence	NOUN
alkej-102	36	33	.	.	PUNCT
alkej-102	37	1	to	to	PART
alkej-102	37	2	do	do	VERB
alkej-102	37	3	this	this	PRON
alkej-102	37	4	,	,	PUNCT
alkej-102	37	5	the	the	DET
alkej-102	37	6	original	original	ADJ
alkej-102	37	7	data	data	NOUN
alkej-102	37	8	is	be	AUX
alkej-102	37	9	not	not	PART
alkej-102	37	10	decimated	decimate	VERB
alkej-102	37	11	.	.	PUNCT
alkej-102	38	1	however	however	ADV
alkej-102	38	2	,	,	PUNCT
alkej-102	38	3	the	the	DET
alkej-102	38	4	filters	filter	NOUN
alkej-102	38	5	at	at	ADP
alkej-102	38	6	each	each	DET
alkej-102	38	7	level	level	NOUN
alkej-102	38	8	are	be	AUX
alkej-102	38	9	modified	modify	VERB
alkej-102	38	10	by	by	ADP
alkej-102	38	11	padding	pad	VERB
alkej-102	38	12	them	they	PRON
alkej-102	38	13	out	out	ADP
alkej-102	38	14	with	with	ADP
alkej-102	38	15	zeros	zero	NOUN
alkej-102	38	16	.	.	PUNCT
alkej-102	39	1	supposing	suppose	VERB
alkej-102	39	2	a	a	DET
alkej-102	39	3	function	function	NOUN
alkej-102	39	4	)	)	PUNCT
alkej-102	39	5	(	(	PUNCT
alkej-102	39	6	xf	xf	PROPN
alkej-102	39	7	is	be	AUX
alkej-102	39	8	projected	project	VERB
alkej-102	39	9	at	at	ADP
alkej-102	39	10	each	each	DET
alkej-102	39	11	step	step	NOUN
alkej-102	39	12	j	j	PROPN
alkej-102	39	13	on	on	ADP
alkej-102	39	14	the	the	DET
alkej-102	39	15	subset	subset	ADJ
alkej-102	39	16	jv	jv	NOUN
alkej-102	39	17	)	)	PUNCT
alkej-102	39	18	(	(	PUNCT
alkej-102	39	19	....	....	SYM
alkej-102	39	20	0123	0123	NUM
alkej-102	39	21	vvvv	vvvv	NOUN
alkej-102	39	22			NOUN
alkej-102	39	23	.	.	PUNCT
alkej-102	40	1	this	this	DET
alkej-102	40	2	projection	projection	NOUN
alkej-102	40	3	is	be	AUX
alkej-102	40	4	defined	define	VERB
alkej-102	40	5	by	by	ADP
alkej-102	40	6	the	the	DET
alkej-102	40	7	scalar	scalar	ADJ
alkej-102	40	8	product	product	NOUN
alkej-102	40	9	kjc	kjc	PROPN
alkej-102	40	10	,	,	PUNCT
alkej-102	40	11	of	of	ADP
alkej-102	40	12	)	)	PUNCT
alkej-102	40	13	(	(	PUNCT
alkej-102	40	14	xf	xf	PROPN
alkej-102	40	15	with	with	ADP
alkej-102	40	16	the	the	DET
alkej-102	40	17	scaling	scale	VERB
alkej-102	40	18	function	function	NOUN
alkej-102	40	19	)	)	PUNCT
alkej-102	40	20	(	(	PUNCT
alkej-102	40	21	x	x	NOUN
alkej-102	40	22	which	which	PRON
alkej-102	40	23	is	be	AUX
alkej-102	40	24	dilated	dilate	VERB
alkej-102	40	25	and	and	CCONJ
alkej-102	40	26	translated	translate	VERB
alkej-102	40	27	.	.	PUNCT
alkej-102	41	1			PROPN
alkej-102	41	2	)	)	PUNCT
alkej-102	41	3	(	(	PUNCT
alkej-102	41	4	)	)	PUNCT
alkej-102	41	5	,	,	PUNCT
alkej-102	41	6	(	(	PUNCT
alkej-102	41	7	,	,	PUNCT
alkej-102	41	8	,	,	PUNCT
alkej-102	41	9	xxfc	xxfc	PROPN
alkej-102	41	10	kjkj	kjkj	VERB
alkej-102	41	11			PROPN
alkej-102	41	12	...	...	PUNCT
alkej-102	41	13	(	(	PUNCT
alkej-102	41	14	1	1	NUM
alkej-102	41	15	)	)	PUNCT
alkej-102	41	16	)	)	PUNCT
alkej-102	41	17	2(2	2(2	NUM
alkej-102	41	18	)	)	PUNCT
alkej-102	41	19	(	(	PUNCT
alkej-102	41	20	,	,	PUNCT
alkej-102	41	21	kxx	kxx	PROPN
alkej-102	41	22	jj	jj	PROPN
alkej-102	41	23	kj	kj	PROPN
alkej-102	41	24			PROPN
alkej-102	41	25			NUM
alkej-102	41	26			PROPN
alkej-102	41	27	...	...	PUNCT
alkej-102	41	28	(	(	PUNCT
alkej-102	41	29	2	2	X
alkej-102	41	30	)	)	PUNCT
alkej-102	41	31	where	where	SCONJ
alkej-102	41	32	)	)	PUNCT
alkej-102	41	33	(	(	PUNCT
alkej-102	41	34	x	x	PROPN
alkej-102	41	35	is	be	AUX
alkej-102	41	36	the	the	DET
alkej-102	41	37	scaling	scale	VERB
alkej-102	41	38	function	function	NOUN
alkej-102	41	39	,	,	PUNCT
alkej-102	41	40	which	which	PRON
alkej-102	41	41	is	be	AUX
alkej-102	41	42	a	a	DET
alkej-102	41	43	low	low	ADJ
alkej-102	41	44	-	-	PUNCT
alkej-102	41	45	pass	pass	NOUN
alkej-102	41	46	filter	filter	NOUN
alkej-102	41	47	.	.	PUNCT
alkej-102	42	1	kjc	kjc	PROPN
alkej-102	42	2	,	,	PUNCT
alkej-102	42	3	is	be	AUX
alkej-102	42	4	also	also	ADV
alkej-102	42	5	called	call	VERB
alkej-102	42	6	a	a	DET
alkej-102	42	7	discrete	discrete	ADJ
alkej-102	42	8	approximation	approximation	NOUN
alkej-102	42	9	at	at	ADP
alkej-102	42	10	the	the	DET
alkej-102	42	11	resolution	resolution	NOUN
alkej-102	42	12	j2	j2	NOUN
alkej-102	42	13	.	.	PUNCT
alkej-102	43	1	if	if	SCONJ
alkej-102	43	2	)	)	PUNCT
alkej-102	43	3	(	(	PUNCT
alkej-102	43	4	x	x	X
alkej-102	43	5	is	be	AUX
alkej-102	43	6	the	the	DET
alkej-102	43	7	wavelet	wavelet	NOUN
alkej-102	43	8	function	function	NOUN
alkej-102	43	9	,	,	PUNCT
alkej-102	43	10	the	the	DET
alkej-102	43	11	wavelet	wavelet	NOUN
alkej-102	43	12	coefficients	coefficient	NOUN
alkej-102	43	13	are	be	AUX
alkej-102	43	14	obtained	obtain	VERB
alkej-102	43	15	by	by	ADP
alkej-102	43	16			PROPN
alkej-102	43	17			PROPN
alkej-102	43	18	)	)	PUNCT
alkej-102	43	19	2(2	2(2	NUM
alkej-102	43	20	)	)	PUNCT
alkej-102	43	21	,	,	PUNCT
alkej-102	43	22	(	(	PUNCT
alkej-102	43	23	,	,	PUNCT
alkej-102	43	24	kxxf	kxxf	PROPN
alkej-102	43	25	jj	jj	PROPN
alkej-102	43	26	kj	kj	PROPN
alkej-102	43	27			PROPN
alkej-102	43	28	...	...	PUNCT
alkej-102	43	29	(	(	PUNCT
alkej-102	43	30	3	3	X
alkej-102	43	31	)	)	PUNCT
alkej-102	43	32	kj	kj	NOUN
alkej-102	43	33	,	,	PUNCT
alkej-102	43	34			PROPN
alkej-102	43	35	is	be	AUX
alkej-102	43	36	called	call	VERB
alkej-102	43	37	the	the	DET
alkej-102	43	38	discrete	discrete	ADJ
alkej-102	43	39	detail	detail	NOUN
alkej-102	43	40	signal	signal	NOUN
alkej-102	43	41	at	at	ADP
alkej-102	43	42	the	the	DET
alkej-102	43	43	resolution	resolution	NOUN
alkej-102	43	44	j2	j2	PROPN
alkej-102	43	45	.	.	PUNCT
alkej-102	44	1	as	as	ADP
alkej-102	44	2	the	the	DET
alkej-102	44	3	scaling	scale	VERB
alkej-102	44	4	function	function	NOUN
alkej-102	44	5	)	)	PUNCT
alkej-102	44	6	(	(	PUNCT
alkej-102	44	7	x	x	PROPN
alkej-102	44	8	has	have	VERB
alkej-102	44	9	the	the	DET
alkej-102	44	10	following	follow	VERB
alkej-102	44	11	property	property	NOUN
alkej-102	44	12	:	:	PUNCT
alkej-102	44	13			X
alkej-102	44	14			ADJ
alkej-102	44	15	n	n	CCONJ
alkej-102	44	16	nxnh	nxnh	VERB
alkej-102	44	17	x	x	X
alkej-102	44	18	)	)	PUNCT
alkej-102	44	19	(	(	PUNCT
alkej-102	44	20	)	)	PUNCT
alkej-102	44	21	(	(	PUNCT
alkej-102	44	22	)	)	PUNCT
alkej-102	44	23	2	2	NUM
alkej-102	44	24	(	(	PUNCT
alkej-102	44	25	2	2	NUM
alkej-102	44	26	1	1	NUM
alkej-102	44	27			NUM
alkej-102	44	28	h	h	NOUN
alkej-102	44	29	(	(	PUNCT
alkej-102	44	30	n	n	CCONJ
alkej-102	44	31	)	)	PUNCT
alkej-102	44	32	represents	represent	VERB
alkej-102	44	33	the	the	DET
alkej-102	44	34	scaling	scale	VERB
alkej-102	44	35	coefficients	coefficient	NOUN
alkej-102	44	36	.	.	PUNCT
alkej-102	45	1	kjc	kjc	PROPN
alkej-102	45	2	,	,	PUNCT
alkej-102	45	3	1	1	NUM
alkej-102	45	4	can	can	AUX
alkej-102	45	5	be	be	AUX
alkej-102	45	6	obtained	obtain	VERB
alkej-102	45	7	by	by	ADP
alkej-102	45	8	direct	direct	ADJ
alkej-102	45	9	computation	computation	NOUN
alkej-102	45	10	from	from	ADP
alkej-102	45	11	kjc	kjc	PROPN
alkej-102	45	12	,	,	PUNCT
alkej-102	45	13	.	.	PUNCT
alkej-102	46	1			PROPN
alkej-102	46	2			VERB
alkej-102	46	3			ADJ
alkej-102	46	4			NOUN
alkej-102	46	5	n	n	CCONJ
alkej-102	46	6	n	n	CCONJ
alkej-102	46	7	njkj	njkj	NOUN
alkej-102	46	8	nxng	nxng	ADJ
alkej-102	46	9	x	x	PUNCT
alkej-102	46	10	andcknhc	andcknhc	NOUN
alkej-102	46	11	)	)	PUNCT
alkej-102	46	12	(	(	PUNCT
alkej-102	46	13	)	)	PUNCT
alkej-102	46	14	(	(	PUNCT
alkej-102	46	15	)	)	PUNCT
alkej-102	46	16	2	2	NUM
alkej-102	46	17	(	(	PUNCT
alkej-102	46	18	2	2	NUM
alkej-102	46	19	1	1	NUM
alkej-102	46	20	)	)	PUNCT
alkej-102	46	21	2	2	NUM
alkej-102	46	22	(	(	PUNCT
alkej-102	46	23	,	,	PUNCT
alkej-102	46	24	,	,	PUNCT
alkej-102	46	25	1	1	NUM
alkej-102	46	26			X
alkej-102	46	27	...	...	PUNCT
alkej-102	46	28	(	(	PUNCT
alkej-102	46	29	4	4	X
alkej-102	46	30	)	)	PUNCT
alkej-102	46	31	g	g	NOUN
alkej-102	46	32	(	(	PUNCT
alkej-102	46	33	n	n	CCONJ
alkej-102	46	34	)	)	PUNCT
alkej-102	46	35	represents	represent	VERB
alkej-102	46	36	the	the	DET
alkej-102	46	37	wavelet	wavelet	NOUN
alkej-102	46	38	coefficients	coefficient	NOUN
alkej-102	46	39	.	.	PUNCT
alkej-102	47	1	the	the	DET
alkej-102	47	2	scalar	scalar	ADJ
alkej-102	47	3	products	product	NOUN
alkej-102	47	4			PROPN
alkej-102	47	5			NOUN
alkej-102	47	6	)	)	PUNCT
alkej-102	47	7	2(2	2(2	NUM
alkej-102	47	8	)	)	PUNCT
alkej-102	47	9	,	,	PUNCT
alkej-102	47	10	(	(	PUNCT
alkej-102	47	11	)	)	PUNCT
alkej-102	47	12	1()1	1()1	NUM
alkej-102	47	13	(	(	PUNCT
alkej-102	47	14	,	,	PUNCT
alkej-102	47	15	kxxf	kxxf	PROPN
alkej-102	47	16	jj	jj	PROPN
alkej-102	47	17	kj	kj	PROPN
alkej-102	47	18			PROPN
alkej-102	47	19	are	be	AUX
alkej-102	47	20	computed	compute	VERB
alkej-102	47	21	with	with	ADP
alkej-102	47	22			X
alkej-102	47	23			PROPN
alkej-102	47	24	n	n	CCONJ
alkej-102	47	25	njkj	njkj	NOUN
alkej-102	47	26	ckng	ckng	NOUN
alkej-102	47	27	,	,	PUNCT
alkej-102	47	28	,	,	PUNCT
alkej-102	47	29	1	1	NUM
alkej-102	47	30	)	)	PUNCT
alkej-102	47	31	2(	2(	NUM
alkej-102	47	32	...	...	PUNCT
alkej-102	47	33	(	(	PUNCT
alkej-102	47	34	5	5	X
alkej-102	47	35	)	)	PUNCT
alkej-102	47	36	equations	equation	NOUN
alkej-102	47	37	(	(	PUNCT
alkej-102	47	38	4	4	NUM
alkej-102	47	39	)	)	PUNCT
alkej-102	47	40	and	and	CCONJ
alkej-102	47	41	(	(	PUNCT
alkej-102	47	42	5	5	X
alkej-102	47	43	)	)	PUNCT
alkej-102	47	44	are	be	AUX
alkej-102	47	45	the	the	DET
alkej-102	47	46	multiresolution	multiresolution	NOUN
alkej-102	47	47	algorithm	algorithm	NOUN
alkej-102	47	48	of	of	ADP
alkej-102	47	49	the	the	DET
alkej-102	47	50	traditional	traditional	ADJ
alkej-102	47	51	dwt	dwt	NOUN
alkej-102	47	52	.	.	PUNCT
alkej-102	48	1	in	in	ADP
alkej-102	48	2	this	this	DET
alkej-102	48	3	transform	transform	NOUN
alkej-102	48	4	,	,	PUNCT
alkej-102	48	5	a	a	DET
alkej-102	48	6	downsampling	downsample	VERB
alkej-102	48	7	algorithm	algorithm	NOUN
alkej-102	48	8	is	be	AUX
alkej-102	48	9	used	use	VERB
alkej-102	48	10	to	to	PART
alkej-102	48	11	perform	perform	VERB
alkej-102	48	12	the	the	DET
alkej-102	48	13	transformation	transformation	NOUN
alkej-102	48	14	.	.	PUNCT
alkej-102	49	1	that	that	PRON
alkej-102	49	2	is	is	ADV
alkej-102	49	3	,	,	PUNCT
alkej-102	49	4	one	one	NUM
alkej-102	49	5	point	point	NOUN
alkej-102	49	6	out	out	ADP
alkej-102	49	7	of	of	ADP
alkej-102	49	8	two	two	NUM
alkej-102	49	9	is	be	AUX
alkej-102	49	10	kept	keep	VERB
alkej-102	49	11	during	during	ADP
alkej-102	49	12	transformation	transformation	NOUN
alkej-102	49	13	.	.	PUNCT
alkej-102	50	1	therefore	therefore	ADV
alkej-102	50	2	,	,	PUNCT
alkej-102	50	3	the	the	DET
alkej-102	50	4	whole	whole	ADJ
alkej-102	50	5	length	length	NOUN
alkej-102	50	6	of	of	ADP
alkej-102	50	7	the	the	DET
alkej-102	50	8	function	function	NOUN
alkej-102	50	9	will	will	AUX
alkej-102	50	10	be	be	AUX
alkej-102	50	11	reduced	reduce	VERB
alkej-102	50	12	by	by	ADP
alkej-102	50	13	half	half	NOUN
alkej-102	50	14	after	after	ADP
alkej-102	50	15	the	the	DET
alkej-102	50	16	transformation	transformation	NOUN
alkej-102	50	17	.	.	PUNCT
alkej-102	51	1	this	this	DET
alkej-102	51	2	process	process	NOUN
alkej-102	51	3	continues	continue	VERB
alkej-102	51	4	until	until	SCONJ
alkej-102	51	5	the	the	DET
alkej-102	51	6	length	length	NOUN
alkej-102	51	7	of	of	ADP
alkej-102	51	8	the	the	DET
alkej-102	51	9	function	function	NOUN
alkej-102	51	10	becomes	become	VERB
alkej-102	51	11	one	one	NUM
alkej-102	51	12	.	.	PUNCT
alkej-102	52	1	however	however	ADV
alkej-102	52	2	,	,	PUNCT
alkej-102	52	3	for	for	ADP
alkej-102	52	4	stationary	stationary	ADJ
alkej-102	52	5	or	or	CCONJ
alkej-102	52	6	redundant	redundant	ADJ
alkej-102	52	7	transform	transform	NOUN
alkej-102	52	8	,	,	PUNCT
alkej-102	52	9	instead	instead	ADV
alkej-102	52	10	of	of	ADP
alkej-102	52	11	downsampling	downsample	VERB
alkej-102	52	12	,	,	PUNCT
alkej-102	52	13	an	an	DET
alkej-102	52	14	upsampling	upsample	VERB
alkej-102	52	15	procedure	procedure	NOUN
alkej-102	52	16	is	be	AUX
alkej-102	52	17	carried	carry	VERB
alkej-102	52	18	out	out	ADP
alkej-102	52	19	before	before	ADP
alkej-102	52	20	performing	perform	VERB
alkej-102	52	21	filter	filter	NOUN
alkej-102	52	22	convolution	convolution	NOUN
alkej-102	52	23	at	at	ADP
alkej-102	52	24	each	each	DET
alkej-102	52	25	scale	scale	NOUN
alkej-102	52	26	.	.	PUNCT
alkej-102	53	1	the	the	DET
alkej-102	53	2	distance	distance	NOUN
alkej-102	53	3	between	between	ADP
alkej-102	53	4	samples	sample	NOUN
alkej-102	53	5	is	be	AUX
alkej-102	53	6	increased	increase	VERB
alkej-102	53	7	by	by	ADP
alkej-102	53	8	a	a	DET
alkej-102	53	9	factor	factor	NOUN
alkej-102	53	10	of	of	ADP
alkej-102	53	11	two	two	NUM
alkej-102	53	12	from	from	ADP
alkej-102	53	13	scale	scale	NOUN
alkej-102	53	14	to	to	ADP
alkej-102	53	15	the	the	DET
alkej-102	53	16	next	next	ADJ
alkej-102	53	17	.	.	PUNCT
alkej-102	54	1	kjc	kjc	PROPN
alkej-102	54	2	,	,	PUNCT
alkej-102	54	3	1	1	NUM
alkej-102	54	4	is	be	AUX
alkej-102	54	5	obtained	obtain	VERB
alkej-102	54	6	by	by	ADP
alkej-102	54	7			X
alkej-102	54	8			PROPN
alkej-102	54	9			PROPN
alkej-102	54	10	l	l	NOUN
alkej-102	54	11	lkjkj	lkjkj	ADJ
alkej-102	54	12	jclhc	jclhc	NOUN
alkej-102	54	13	2,,1	2,,1	NUM
alkej-102	54	14	)	)	PUNCT
alkej-102	54	15	(	(	PUNCT
alkej-102	54	16	...	...	PUNCT
alkej-102	54	17	(	(	PUNCT
alkej-102	54	18	6	6	NUM
alkej-102	54	19	)	)	PUNCT
alkej-102	54	20	and	and	CCONJ
alkej-102	54	21	the	the	DET
alkej-102	54	22	discrete	discrete	ADJ
alkej-102	54	23	wavelet	wavelet	NOUN
alkej-102	54	24	coefficients	coefficient	NOUN
alkej-102	54	25			X
alkej-102	55	1			ADJ
alkej-102	55	2			PROPN
alkej-102	55	3	l	l	NOUN
alkej-102	55	4	lkjkj	lkjkj	ADJ
alkej-102	55	5	jclg	jclg	NOUN
alkej-102	55	6	2,,1	2,,1	NUM
alkej-102	55	7	)	)	PUNCT
alkej-102	55	8	(	(	PUNCT
alkej-102	55	9			X
alkej-102	55	10	...	...	PUNCT
alkej-102	55	11	(	(	PUNCT
alkej-102	55	12	7	7	X
alkej-102	55	13	)	)	PUNCT
alkej-102	55	14	the	the	DET
alkej-102	55	15	redundancy	redundancy	NOUN
alkej-102	55	16	of	of	ADP
alkej-102	55	17	this	this	DET
alkej-102	55	18	transform	transform	NOUN
alkej-102	55	19	facilitates	facilitate	VERB
alkej-102	55	20	the	the	DET
alkej-102	55	21	identification	identification	NOUN
alkej-102	55	22	of	of	ADP
alkej-102	55	23	salient	salient	NOUN
alkej-102	55	24	features	feature	NOUN
alkej-102	55	25	in	in	ADP
alkej-102	55	26	a	a	DET
alkej-102	55	27	signal	signal	NOUN
alkej-102	55	28	,	,	PUNCT
alkej-102	55	29	especially	especially	ADV
alkej-102	55	30	for	for	ADP
alkej-102	55	31	recognizing	recognize	VERB
alkej-102	55	32	the	the	DET
alkej-102	55	33	noises	noise	NOUN
alkej-102	55	34	.	.	PUNCT
alkej-102	56	1	this	this	PRON
alkej-102	56	2	is	be	AUX
alkej-102	56	3	the	the	DET
alkej-102	56	4	transform	transform	NOUN
alkej-102	56	5	for	for	ADP
alkej-102	56	6	one	one	NUM
alkej-102	56	7	-	-	PUNCT
alkej-102	56	8	dimensional	dimensional	ADJ
alkej-102	56	9	signal	signal	NOUN
alkej-102	56	10	.	.	PUNCT
alkej-102	57	1	for	for	ADP
alkej-102	57	2	a	a	DET
alkej-102	57	3	twodimensional	twodimensional	ADJ
alkej-102	57	4	image	image	NOUN
alkej-102	57	5	,	,	PUNCT
alkej-102	57	6	we	we	PRON
alkej-102	57	7	separate	separate	VERB
alkej-102	57	8	the	the	DET
alkej-102	57	9	variables	variable	NOUN
alkej-102	57	10	x	x	PUNCT
alkej-102	57	11	and	and	CCONJ
alkej-102	57	12	y	y	PROPN
alkej-102	57	13	and	and	CCONJ
alkej-102	57	14	have	have	VERB
alkej-102	57	15	the	the	DET
alkej-102	57	16	following	follow	VERB
alkej-102	57	17	wavelets	wavelet	NOUN
alkej-102	57	18	.	.	PUNCT
alkej-102	58	1	iman	iman	PROPN
alkej-102	58	2	m.g	m.g	PROPN
alkej-102	58	3	.	.	PROPN
alkej-102	58	4	alwan	alwan	PROPN
alkej-102	58	5	al	al	PROPN
alkej-102	58	6	-	-	PUNCT
alkej-102	58	7	khwarizmi	khwarizmi	PROPN
alkej-102	58	8	engineering	engineering	NOUN
alkej-102	58	9	journal	journal	PROPN
alkej-102	58	10	,	,	PUNCT
alkej-102	58	11	vol	vol	NOUN
alkej-102	58	12	.	.	PROPN
alkej-102	58	13	8	8	NUM
alkej-102	58	14	,	,	PUNCT
alkej-102	58	15	no	no	INTJ
alkej-102	58	16	.	.	PUNCT
alkej-102	59	1	1,pp	1,pp	NUM
alkej-102	59	2	18	18	NUM
alkej-102	59	3	26	26	NUM
alkej-102	59	4	(	(	PUNCT
alkej-102	59	5	2012	2012	NUM
alkej-102	59	6	)	)	PUNCT
alkej-102	59	7	20	20	NUM
alkej-102	59	8	—	—	PUNCT
alkej-102	59	9	vertical	vertical	ADJ
alkej-102	59	10	wavelet	wavelet	NOUN
alkej-102	59	11	:	:	PUNCT
alkej-102	59	12	)	)	PUNCT
alkej-102	59	13	(	(	PUNCT
alkej-102	59	14	)	)	PUNCT
alkej-102	59	15	(	(	PUNCT
alkej-102	59	16	)	)	PUNCT
alkej-102	59	17	,	,	PUNCT
alkej-102	59	18	(	(	PUNCT
alkej-102	59	19	1	1	NUM
alkej-102	59	20	yxyx	yxyx	NOUN
alkej-102	59	21			ADP
alkej-102	59	22			PROPN
alkej-102	59	23	—	—	PUNCT
alkej-102	59	24	horizontal	horizontal	ADJ
alkej-102	59	25	wavelet	wavelet	NOUN
alkej-102	59	26	:	:	PUNCT
alkej-102	59	27	)	)	PUNCT
alkej-102	59	28	(	(	PUNCT
alkej-102	59	29	)	)	PUNCT
alkej-102	59	30	(	(	PUNCT
alkej-102	59	31	)	)	PUNCT
alkej-102	59	32	,	,	PUNCT
alkej-102	59	33	(	(	PUNCT
alkej-102	59	34	2	2	NUM
alkej-102	59	35	yxyx	yxyx	NOUN
alkej-102	59	36			NOUN
alkej-102	59	37			NUM
alkej-102	59	38	—	—	PUNCT
alkej-102	59	39	diagonal	diagonal	ADJ
alkej-102	59	40	wavelet	wavelet	NOUN
alkej-102	59	41	:	:	PUNCT
alkej-102	59	42	)	)	PUNCT
alkej-102	59	43	(	(	PUNCT
alkej-102	59	44	)	)	PUNCT
alkej-102	59	45	(	(	PUNCT
alkej-102	59	46	)	)	PUNCT
alkej-102	59	47	,	,	PUNCT
alkej-102	59	48	(	(	PUNCT
alkej-102	59	49	3	3	NUM
alkej-102	59	50	yxyx	yxyx	NOUN
alkej-102	59	51			PROPN
alkej-102	59	52			PRON
alkej-102	59	53	thus	thus	ADV
alkej-102	59	54	,	,	PUNCT
alkej-102	59	55	the	the	DET
alkej-102	59	56	detail	detail	NOUN
alkej-102	59	57	signal	signal	NOUN
alkej-102	59	58	is	be	AUX
alkej-102	59	59	contained	contain	VERB
alkej-102	59	60	in	in	ADP
alkej-102	59	61	three	three	NUM
alkej-102	59	62	subimages	subimage	NOUN
alkej-102	59	63	[	[	X
alkej-102	59	64	8	8	NUM
alkej-102	59	65	]	]	PUNCT
alkej-102	59	66	.	.	PUNCT
alkej-102	60	1			PROPN
alkej-102	60	2			X
alkej-102	60	3			ADJ
alkej-102	60	4			PROPN
alkej-102	60	5			ADJ
alkej-102	60	6			PROPN
alkej-102	60	7			PROPN
alkej-102	60	8			PROPN
alkej-102	60	9	x	x	PUNCT
alkej-102	60	10	y	y	PROPN
alkej-102	60	11	j	j	PROPN
alkej-102	60	12	l	l	PROPN
alkej-102	60	13	l	l	NOUN
alkej-102	60	14	yxkjyxyxj	yxkjyxyxj	NOUN
alkej-102	60	15	llclhlgkk	llclhlgkk	PROPN
alkej-102	60	16	)	)	PUNCT
alkej-102	60	17	,	,	PUNCT
alkej-102	60	18	(	(	PUNCT
alkej-102	60	19	)	)	PUNCT
alkej-102	60	20	(	(	PUNCT
alkej-102	60	21	)	)	PUNCT
alkej-102	60	22	(	(	PUNCT
alkej-102	60	23	)	)	PUNCT
alkej-102	60	24	,	,	PUNCT
alkej-102	60	25	(	(	PUNCT
alkej-102	60	26	2	2	NUM
alkej-102	60	27	,	,	PUNCT
alkej-102	60	28	1	1	NUM
alkej-102	60	29	1	1	NUM
alkej-102	60	30	..	..	PUNCT
alkej-102	60	31	(	(	PUNCT
alkej-102	60	32	8)	8)	NUM
alkej-102	60	33			X
alkej-102	60	34			X
alkej-102	60	35			ADJ
alkej-102	60	36			PROPN
alkej-102	60	37			ADJ
alkej-102	60	38			PROPN
alkej-102	60	39			PROPN
alkej-102	60	40			PROPN
alkej-102	60	41	x	x	PUNCT
alkej-102	60	42	y	y	PROPN
alkej-102	60	43	j	j	PROPN
alkej-102	60	44	l	l	PROPN
alkej-102	60	45	l	l	NOUN
alkej-102	60	46	yxkjyxyxj	yxkjyxyxj	NOUN
alkej-102	60	47	llclglhkk	llclglhkk	PROPN
alkej-102	60	48	)	)	PUNCT
alkej-102	60	49	,	,	PUNCT
alkej-102	60	50	(	(	PUNCT
alkej-102	60	51	)	)	PUNCT
alkej-102	60	52	(	(	PUNCT
alkej-102	60	53	)	)	PUNCT
alkej-102	60	54	(	(	PUNCT
alkej-102	60	55	)	)	PUNCT
alkej-102	60	56	,	,	PUNCT
alkej-102	60	57	(	(	PUNCT
alkej-102	60	58	2	2	NUM
alkej-102	60	59	,	,	PUNCT
alkej-102	60	60	2	2	NUM
alkej-102	60	61	1	1	NUM
alkej-102	60	62	...	...	PUNCT
alkej-102	60	63	(	(	PUNCT
alkej-102	60	64	9	9	X
alkej-102	60	65	)	)	PUNCT
alkej-102	60	66			X
alkej-102	60	67			X
alkej-102	60	68			ADJ
alkej-102	60	69			PROPN
alkej-102	60	70			ADJ
alkej-102	60	71			PROPN
alkej-102	60	72			PROPN
alkej-102	60	73			PROPN
alkej-102	60	74	x	x	PUNCT
alkej-102	60	75	y	y	PROPN
alkej-102	60	76	j	j	PROPN
alkej-102	60	77	l	l	PROPN
alkej-102	60	78	l	l	X
alkej-102	60	79	yxkjyxyxj	yxkjyxyxj	NOUN
alkej-102	60	80	llclglgkk	llclglgkk	PROPN
alkej-102	60	81	)	)	PUNCT
alkej-102	60	82	,	,	PUNCT
alkej-102	60	83	(	(	PUNCT
alkej-102	60	84	)	)	PUNCT
alkej-102	60	85	(	(	PUNCT
alkej-102	60	86	)	)	PUNCT
alkej-102	60	87	(	(	PUNCT
alkej-102	60	88	)	)	PUNCT
alkej-102	60	89	,	,	PUNCT
alkej-102	60	90	(	(	PUNCT
alkej-102	60	91	2	2	NUM
alkej-102	60	92	,	,	PUNCT
alkej-102	60	93	3	3	NUM
alkej-102	60	94	1	1	NUM
alkej-102	60	95	...	...	PUNCT
alkej-102	60	96	(	(	PUNCT
alkej-102	60	97	10	10	NUM
alkej-102	60	98	)	)	PUNCT
alkej-102	60	99	3	3	NUM
alkej-102	60	100	.	.	X
alkej-102	61	1	implementation	implementation	NOUN
alkej-102	61	2	of	of	ADP
alkej-102	61	3	the	the	DET
alkej-102	61	4	proposed	propose	VERB
alkej-102	61	5	algorithm	algorithm	NOUN
alkej-102	61	6	this	this	DET
alkej-102	61	7	section	section	NOUN
alkej-102	61	8	,	,	PUNCT
alkej-102	61	9	describes	describe	VERB
alkej-102	61	10	the	the	DET
alkej-102	61	11	method	method	NOUN
alkej-102	61	12	for	for	ADP
alkej-102	61	13	computing	compute	VERB
alkej-102	61	14	the	the	DET
alkej-102	61	15	various	various	ADJ
alkej-102	61	16	parameters	parameter	NOUN
alkej-102	61	17	used	use	VERB
alkej-102	61	18	to	to	PART
alkej-102	61	19	compute	compute	VERB
alkej-102	61	20	the	the	DET
alkej-102	61	21	threshold	threshold	NOUN
alkej-102	61	22	and	and	CCONJ
alkej-102	61	23	the	the	DET
alkej-102	61	24	image	image	NOUN
alkej-102	61	25	denoising	denoising	NOUN
alkej-102	61	26	algorithm	algorithm	NOUN
alkej-102	61	27	.	.	PUNCT
alkej-102	62	1	the	the	DET
alkej-102	62	2	swt	swt	PROPN
alkej-102	62	3	is	be	AUX
alkej-102	62	4	used	use	VERB
alkej-102	62	5	for	for	ADP
alkej-102	62	6	the	the	DET
alkej-102	62	7	recovery	recovery	NOUN
alkej-102	62	8	of	of	ADP
alkej-102	62	9	the	the	DET
alkej-102	62	10	corrupted	corrupted	ADJ
alkej-102	62	11	image	image	NOUN
alkej-102	62	12	with	with	ADP
alkej-102	62	13	adaptive	adaptive	ADJ
alkej-102	62	14	wiener	wiener	NOUN
alkej-102	62	15	filter	filter	NOUN
alkej-102	62	16	.	.	PUNCT
alkej-102	63	1	wiener	wiener	NOUN
alkej-102	63	2	filter	filter	NOUN
alkej-102	63	3	is	be	AUX
alkej-102	63	4	a	a	DET
alkej-102	63	5	minimum	minimum	ADJ
alkej-102	63	6	mean	mean	NOUN
alkej-102	63	7	square	square	ADJ
alkej-102	63	8	error	error	NOUN
alkej-102	63	9	filter	filter	NOUN
alkej-102	63	10	.	.	PUNCT
alkej-102	64	1	it	it	PRON
alkej-102	64	2	has	have	VERB
alkej-102	64	3	capabilities	capability	NOUN
alkej-102	64	4	of	of	ADP
alkej-102	64	5	handling	handle	VERB
alkej-102	64	6	both	both	CCONJ
alkej-102	64	7	the	the	DET
alkej-102	64	8	degradation	degradation	NOUN
alkej-102	64	9	function	function	NOUN
alkej-102	64	10	as	as	ADV
alkej-102	64	11	well	well	ADV
alkej-102	64	12	as	as	ADP
alkej-102	64	13	the	the	DET
alkej-102	64	14	noise	noise	NOUN
alkej-102	64	15	.	.	PUNCT
alkej-102	65	1	the	the	DET
alkej-102	65	2	wiener	wiener	NOUN
alkej-102	65	3	filter	filter	NOUN
alkej-102	65	4	in	in	ADP
alkej-102	65	5	the	the	DET
alkej-102	65	6	fourier	fourier	ADJ
alkej-102	65	7	domain	domain	NOUN
alkej-102	65	8	is	be	AUX
alkej-102	65	9	given	give	VERB
alkej-102	65	10	by	by	ADP
alkej-102	65	11	the	the	DET
alkej-102	65	12	expression	expression	NOUN
alkej-102	65	13	:	:	PUNCT
alkej-102	65	14	)	)	PUNCT
alkej-102	65	15	,	,	PUNCT
alkej-102	65	16	(	(	PUNCT
alkej-102	65	17	)	)	PUNCT
alkej-102	65	18	,	,	PUNCT
alkej-102	65	19	(	(	PUNCT
alkej-102	65	20	)	)	PUNCT
alkej-102	65	21	,	,	PUNCT
alkej-102	65	22	(	(	PUNCT
alkej-102	65	23	)	)	PUNCT
alkej-102	65	24	,	,	PUNCT
alkej-102	65	25	(	(	PUNCT
alkej-102	65	26	)	)	PUNCT
alkej-102	65	27	,	,	PUNCT
alkej-102	65	28	(	(	PUNCT
alkej-102	65	29	)	)	PUNCT
alkej-102	65	30	,	,	PUNCT
alkej-102	65	31	(	(	PUNCT
alkej-102	65	32	2	2	NUM
alkej-102	65	33	*	*	PUNCT
alkej-102	65	34	vug	vug	X
alkej-102	65	35	vus	vus	PROPN
alkej-102	65	36	vus	vus	PROPN
alkej-102	65	37	vuh	vuh	PROPN
alkej-102	65	38	vuh	vuh	PROPN
alkej-102	65	39	vuf	vuf	NOUN
alkej-102	66	1	f	f	PROPN
alkej-102	66	2			PROPN
alkej-102	67	1			PROPN
alkej-102	67	2			PUNCT
alkej-102	68	1			NOUN
alkej-102	68	2			PROPN
alkej-102	68	3			PROPN
alkej-102	68	4			X
alkej-102	68	5			NOUN
alkej-102	68	6			NOUN
alkej-102	68	7			NOUN
alkej-102	68	8			NOUN
alkej-102	68	9			NOUN
alkej-102	68	10			NOUN
alkej-102	68	11			PROPN
alkej-102	68	12			ADV
alkej-102	68	13			PROPN
alkej-102	68	14			NUM
alkej-102	68	15	...	...	PUNCT
alkej-102	69	1	(	(	PUNCT
alkej-102	69	2	11	11	NUM
alkej-102	69	3	)	)	PUNCT
alkej-102	69	4	where	where	SCONJ
alkej-102	69	5	h	h	NOUN
alkej-102	69	6	(	(	PUNCT
alkej-102	69	7	u	u	NOUN
alkej-102	69	8	,	,	PUNCT
alkej-102	69	9	v	v	NOUN
alkej-102	69	10	)	)	PUNCT
alkej-102	69	11	is	be	AUX
alkej-102	69	12	the	the	DET
alkej-102	69	13	degraded	degraded	ADJ
alkej-102	69	14	function	function	NOUN
alkej-102	69	15	)	)	PUNCT
alkej-102	69	16	,	,	PUNCT
alkej-102	69	17	(	(	PUNCT
alkej-102	69	18	*	*	PUNCT
alkej-102	69	19	vuh	vuh	NOUN
alkej-102	69	20	is	be	AUX
alkej-102	69	21	the	the	DET
alkej-102	69	22	complex	complex	ADJ
alkej-102	69	23	conjugate	conjugate	NOUN
alkej-102	69	24	of	of	ADP
alkej-102	69	25	h(u	h(u	PROPN
alkej-102	69	26	,	,	PUNCT
alkej-102	69	27	v	v	NOUN
alkej-102	69	28	)	)	PUNCT
alkej-102	69	29	)	)	PUNCT
alkej-102	69	30	,	,	PUNCT
alkej-102	69	31	(	(	PUNCT
alkej-102	69	32	)	)	PUNCT
alkej-102	69	33	,	,	PUNCT
alkej-102	69	34	(	(	PUNCT
alkej-102	69	35	)	)	PUNCT
alkej-102	69	36	,	,	PUNCT
alkej-102	69	37	(	(	PUNCT
alkej-102	69	38	*	*	PUNCT
alkej-102	69	39	2	2	NUM
alkej-102	69	40	vuhvuhvuh	vuhvuhvuh	NOUN
alkej-102	69	41			NOUN
alkej-102	69	42	2	2	NUM
alkej-102	69	43	)	)	PUNCT
alkej-102	69	44	,	,	PUNCT
alkej-102	69	45	(	(	PUNCT
alkej-102	69	46	)	)	PUNCT
alkej-102	69	47	,	,	PUNCT
alkej-102	69	48	(	(	PUNCT
alkej-102	69	49	vunvus	vunvus	NOUN
alkej-102	69	50			PROPN
alkej-102	69	51	is	be	AUX
alkej-102	69	52	the	the	DET
alkej-102	69	53	power	power	NOUN
alkej-102	69	54	spectrum	spectrum	NOUN
alkej-102	69	55	of	of	ADP
alkej-102	69	56	the	the	DET
alkej-102	69	57	noise	noise	NOUN
alkej-102	69	58	.	.	PUNCT
alkej-102	70	1	2	2	NUM
alkej-102	70	2	)	)	PUNCT
alkej-102	70	3	,	,	PUNCT
alkej-102	70	4	(	(	PUNCT
alkej-102	70	5	)	)	PUNCT
alkej-102	70	6	,	,	PUNCT
alkej-102	70	7	(	(	PUNCT
alkej-102	70	8	vufvus	vufvus	NOUN
alkej-102	70	9	f	f	PROPN
alkej-102	70	10			PROPN
alkej-102	70	11	is	be	AUX
alkej-102	70	12	the	the	DET
alkej-102	70	13	power	power	NOUN
alkej-102	70	14	spectral	spectral	ADJ
alkej-102	70	15	density	density	NOUN
alkej-102	70	16	(	(	PUNCT
alkej-102	70	17	psd	psd	NOUN
alkej-102	70	18	)	)	PUNCT
alkej-102	70	19	of	of	ADP
alkej-102	70	20	the	the	DET
alkej-102	70	21	undegraded	undegraded	ADJ
alkej-102	70	22	image	image	NOUN
alkej-102	70	23	.	.	PUNCT
alkej-102	71	1	g(u	g(u	PROPN
alkej-102	71	2	,	,	PUNCT
alkej-102	71	3	v	v	NOUN
alkej-102	71	4	)	)	PUNCT
alkej-102	71	5	is	be	AUX
alkej-102	71	6	the	the	DET
alkej-102	71	7	fourier	fourier	ADJ
alkej-102	71	8	transform	transform	NOUN
alkej-102	71	9	of	of	ADP
alkej-102	71	10	the	the	DET
alkej-102	71	11	degraded	degraded	ADJ
alkej-102	71	12	image	image	NOUN
alkej-102	71	13	.	.	PUNCT
alkej-102	72	1	when	when	SCONJ
alkej-102	72	2	wiener	wiener	NOUN
alkej-102	72	3	filtering	filtering	NOUN
alkej-102	72	4	is	be	AUX
alkej-102	72	5	performed	perform	VERB
alkej-102	72	6	on	on	ADP
alkej-102	72	7	small	small	ADJ
alkej-102	72	8	blocks	block	NOUN
alkej-102	72	9	of	of	ADP
alkej-102	72	10	an	an	DET
alkej-102	72	11	image	image	NOUN
alkej-102	72	12	at	at	ADP
alkej-102	72	13	a	a	DET
alkej-102	72	14	time	time	NOUN
alkej-102	72	15	;	;	PUNCT
alkej-102	72	16	the	the	DET
alkej-102	72	17	method	method	NOUN
alkej-102	72	18	is	be	AUX
alkej-102	72	19	called	call	VERB
alkej-102	72	20	local	local	ADJ
alkej-102	72	21	wiener	wiener	NOUN
alkej-102	72	22	filtering	filtering	NOUN
alkej-102	72	23	.	.	PUNCT
alkej-102	73	1	in	in	ADP
alkej-102	73	2	this	this	DET
alkej-102	73	3	method	method	NOUN
alkej-102	73	4	,	,	PUNCT
alkej-102	73	5	the	the	DET
alkej-102	73	6	psd	psd	NOUN
alkej-102	73	7	of	of	ADP
alkej-102	73	8	the	the	DET
alkej-102	73	9	undegraded	undegraded	ADJ
alkej-102	73	10	image	image	NOUN
alkej-102	73	11	is	be	AUX
alkej-102	73	12	estimated	estimate	VERB
alkej-102	73	13	for	for	ADP
alkej-102	73	14	each	each	DET
alkej-102	73	15	block	block	NOUN
alkej-102	73	16	.	.	PUNCT
alkej-102	74	1	this	this	DET
alkej-102	74	2	calculated	calculate	VERB
alkej-102	74	3	psd	psd	NOUN
alkej-102	74	4	is	be	AUX
alkej-102	74	5	then	then	ADV
alkej-102	74	6	used	use	VERB
alkej-102	74	7	in	in	ADP
alkej-102	74	8	the	the	DET
alkej-102	74	9	expression	expression	NOUN
alkej-102	74	10	of	of	ADP
alkej-102	74	11	the	the	DET
alkej-102	74	12	wiener	wiener	NOUN
alkej-102	74	13	filter	filter	NOUN
alkej-102	74	14	.	.	PUNCT
alkej-102	75	1	thus	thus	ADV
alkej-102	75	2	,	,	PUNCT
alkej-102	75	3	the	the	DET
alkej-102	75	4	local	local	ADJ
alkej-102	75	5	statistics	statistic	NOUN
alkej-102	75	6	are	be	AUX
alkej-102	75	7	also	also	ADV
alkej-102	75	8	accounted	account	VERB
alkej-102	75	9	for	for	ADP
alkej-102	75	10	in	in	ADP
alkej-102	75	11	the	the	DET
alkej-102	75	12	calculation	calculation	NOUN
alkej-102	75	13	of	of	ADP
alkej-102	75	14	the	the	DET
alkej-102	75	15	wiener	wiener	NOUN
alkej-102	75	16	filtered	filter	VERB
alkej-102	75	17	image	image	NOUN
alkej-102	75	18	.	.	PUNCT
alkej-102	76	1	images	image	NOUN
alkej-102	76	2	with	with	ADP
alkej-102	76	3	many	many	ADJ
alkej-102	76	4	edges	edge	NOUN
alkej-102	76	5	are	be	AUX
alkej-102	76	6	handled	handle	VERB
alkej-102	76	7	much	much	ADV
alkej-102	76	8	well	well	ADV
alkej-102	76	9	by	by	ADP
alkej-102	76	10	the	the	DET
alkej-102	76	11	local	local	ADJ
alkej-102	76	12	wiener	wiener	NOUN
alkej-102	76	13	filter	filter	NOUN
alkej-102	76	14	than	than	ADP
alkej-102	76	15	the	the	DET
alkej-102	76	16	global	global	ADJ
alkej-102	76	17	wiener	wiener	NOUN
alkej-102	76	18	filter	filter	NOUN
alkej-102	76	19	.	.	PUNCT
alkej-102	77	1	we	we	PRON
alkej-102	77	2	used	use	VERB
alkej-102	77	3	a	a	DET
alkej-102	77	4	window	window	NOUN
alkej-102	77	5	of	of	ADP
alkej-102	77	6	size	size	NOUN
alkej-102	77	7	3	3	NUM
alkej-102	77	8	x	x	SYM
alkej-102	77	9	3	3	NUM
alkej-102	77	10	in	in	ADP
alkej-102	77	11	the	the	DET
alkej-102	77	12	calculation	calculation	NOUN
alkej-102	77	13	of	of	ADP
alkej-102	77	14	the	the	DET
alkej-102	77	15	local	local	ADJ
alkej-102	77	16	[	[	X
alkej-102	77	17	9	9	NUM
alkej-102	77	18	]	]	PUNCT
alkej-102	77	19	the	the	DET
alkej-102	77	20	threshold	threshold	NOUN
alkej-102	77	21	value	value	NOUN
alkej-102	77	22	(	(	PUNCT
alkej-102	77	23	nst	nst	PROPN
alkej-102	77	24	)	)	PUNCT
alkej-102	77	25	,	,	PUNCT
alkej-102	77	26	which	which	PRON
alkej-102	77	27	is	be	AUX
alkej-102	77	28	adaptive	adaptive	ADJ
alkej-102	77	29	to	to	ADP
alkej-102	77	30	different	different	ADJ
alkej-102	77	31	subband	subband	NOUN
alkej-102	77	32	characteristics	characteristic	NOUN
alkej-102	77	33	,	,	PUNCT
alkej-102	77	34	is	be	AUX
alkej-102	77	35	calculated	calculate	VERB
alkej-102	77	36	by	by	ADP
alkej-102	77	37	normal	normal	ADJ
alkej-102	77	38	shrink	shrink	NOUN
alkej-102	78	1	[	[	X
alkej-102	78	2	4	4	NUM
alkej-102	78	3	]	]	PUNCT
alkej-102	78	4	.	.	PUNCT
alkej-102	79	1			PROPN
alkej-102	80	1			PROPN
alkej-102	80	2			NUM
alkej-102	80	3	y	y	PROPN
alkej-102	80	4	n	n	ADV
alkej-102	80	5	nst	nst	ADP
alkej-102	80	6			PROPN
alkej-102	80	7			PROPN
alkej-102	80	8	2	2	NUM
alkej-102	80	9	...	...	PUNCT
alkej-102	80	10	(	(	PUNCT
alkej-102	80	11	12	12	NUM
alkej-102	80	12	)	)	PUNCT
alkej-102	80	13	where	where	SCONJ
alkej-102	80	14	scale	scale	NOUN
alkej-102	80	15	parameter	parameter	NOUN
alkej-102	80	16			PROPN
alkej-102	80	17	is	be	AUX
alkej-102	80	18	calculated	calculate	VERB
alkej-102	80	19	once	once	ADV
alkej-102	80	20	for	for	ADP
alkej-102	80	21	each	each	DET
alkej-102	80	22	scale	scale	NOUN
alkej-102	80	23	using	use	VERB
alkej-102	80	24	)	)	PUNCT
alkej-102	80	25	/log	/log	SYM
alkej-102	80	26	(	(	PUNCT
alkej-102	80	27	jlk	jlk	NOUN
alkej-102	80	28	...	...	PUNCT
alkej-102	80	29	(	(	PUNCT
alkej-102	80	30	13	13	NUM
alkej-102	80	31	)	)	PUNCT
alkej-102	80	32	where	where	SCONJ
alkej-102	80	33	kl	kl	PROPN
alkej-102	80	34	is	be	AUX
alkej-102	80	35	the	the	DET
alkej-102	80	36	length	length	NOUN
alkej-102	80	37	of	of	ADP
alkej-102	80	38	the	the	DET
alkej-102	80	39	subband	subband	NOUN
alkej-102	80	40	at	at	ADP
alkej-102	80	41	the	the	DET
alkej-102	80	42	thk	thk	PROPN
alkej-102	80	43	scale	scale	NOUN
alkej-102	80	44	,	,	PUNCT
alkej-102	80	45	j	j	PROPN
alkej-102	80	46	is	be	AUX
alkej-102	80	47	the	the	DET
alkej-102	80	48	total	total	ADJ
alkej-102	80	49	number	number	NOUN
alkej-102	80	50	of	of	ADP
alkej-102	80	51	decompositions	decomposition	NOUN
alkej-102	80	52	and	and	CCONJ
alkej-102	80	53	^	^	SYM
alkej-102	80	54	y	y	PROPN
alkej-102	80	55	is	be	AUX
alkej-102	80	56	the	the	DET
alkej-102	80	57	standard	standard	ADJ
alkej-102	80	58	deviation	deviation	NOUN
alkej-102	80	59	of	of	ADP
alkej-102	80	60	the	the	DET
alkej-102	80	61	subband	subband	NOUN
alkej-102	80	62	.	.	PUNCT
alkej-102	81	1	noise	noise	NOUN
alkej-102	81	2	variance	variance	NOUN
alkej-102	81	3	2^	2^	NUM
alkej-102	81	4	n	n	NOUN
alkej-102	81	5	is	be	AUX
alkej-102	81	6	estimated	estimate	VERB
alkej-102	81	7	in	in	ADP
alkej-102	81	8	equation	equation	NOUN
alkej-102	81	9	(	(	PUNCT
alkej-102	81	10	14	14	NUM
alkej-102	81	11	)	)	PUNCT
alkej-102	81	12	,	,	PUNCT
alkej-102	81	13	using	use	VERB
alkej-102	81	14	the	the	DET
alkej-102	81	15	robust	robust	ADJ
alkej-102	81	16	and	and	CCONJ
alkej-102	81	17	accurate	accurate	ADJ
alkej-102	81	18	median	median	ADJ
alkej-102	81	19	estimator	estimator	NOUN
alkej-102	81	20	of	of	ADP
alkej-102	81	21	the	the	DET
alkej-102	81	22	suddand	suddand	NOUN
alkej-102	81	23	.	.	PUNCT
alkej-102	82	1	6745.0	6745.0	NUM
alkej-102	82	2	)	)	PUNCT
alkej-102	82	3	(	(	PUNCT
alkej-102	82	4	2^	2^	NUM
alkej-102	82	5	i	i	PRON
alkej-102	82	6	n	n	VERB
alkej-102	82	7	ymedian	ymedian	NOUN
alkej-102	82	8			PUNCT
alkej-102	82	9	...	...	PUNCT
alkej-102	82	10	(	(	PUNCT
alkej-102	82	11	14	14	NUM
alkej-102	82	12	)	)	PUNCT
alkej-102	82	13	iy	iy	VERB
alkej-102	82	14	each	each	DET
alkej-102	82	15	subband	subband	NOUN
alkej-102	82	16	where	where	SCONJ
alkej-102	82	17	0.6745	0.6745	NUM
alkej-102	82	18	is	be	AUX
alkej-102	82	19	the	the	DET
alkej-102	82	20	experiential	experiential	ADJ
alkej-102	82	21	value	value	NOUN
alkej-102	82	22	[	[	X
alkej-102	82	23	10	10	NUM
alkej-102	82	24	]	]	PUNCT
alkej-102	82	25	.	.	PUNCT
alkej-102	83	1	we	we	PRON
alkej-102	83	2	have	have	AUX
alkej-102	83	3	actually	actually	ADV
alkej-102	83	4	applied	apply	VERB
alkej-102	83	5	wiener	wiener	NOUN
alkej-102	83	6	filter	filter	NOUN
alkej-102	83	7	for	for	ADP
alkej-102	83	8	the	the	DET
alkej-102	83	9	image	image	NOUN
alkej-102	83	10	obtained	obtain	VERB
alkej-102	83	11	from	from	ADP
alkej-102	83	12	(	(	PUNCT
alkej-102	83	13	ll	ll	AUX
alkej-102	83	14	subband	subband	VERB
alkej-102	83	15	only	only	ADV
alkej-102	83	16	while	while	SCONJ
alkej-102	83	17	maintaining	maintain	VERB
alkej-102	83	18	other	other	ADJ
alkej-102	83	19	subbands	subband	NOUN
alkej-102	83	20	equal	equal	ADJ
alkej-102	83	21	to	to	ADP
alkej-102	83	22	zero	zero	NUM
alkej-102	83	23	)	)	PUNCT
alkej-102	83	24	in	in	ADP
alkej-102	83	25	the	the	DET
alkej-102	83	26	spatial	spatial	ADJ
alkej-102	83	27	domain	domain	NOUN
alkej-102	83	28	by	by	ADP
alkej-102	83	29	applying	apply	VERB
alkej-102	83	30	inverse	inverse	NOUN
alkej-102	83	31	stationary	stationary	ADJ
alkej-102	83	32	wavelet	wavelet	NOUN
alkej-102	83	33	transform	transform	NOUN
alkej-102	83	34	in	in	ADP
alkej-102	83	35	order	order	NOUN
alkej-102	83	36	to	to	PART
alkej-102	83	37	remove	remove	VERB
alkej-102	83	38	the	the	DET
alkej-102	83	39	residual	residual	ADJ
alkej-102	83	40	noise	noise	NOUN
alkej-102	83	41	in	in	ADP
alkej-102	83	42	the	the	DET
alkej-102	83	43	low	low	ADJ
alkej-102	83	44	frequency	frequency	NOUN
alkej-102	83	45	subband	subband	NOUN
alkej-102	83	46	in	in	ADP
alkej-102	83	47	addition	addition	NOUN
alkej-102	83	48	for	for	ADP
alkej-102	83	49	applying	apply	VERB
alkej-102	83	50	softthreshold	softthreshold	NOUN
alkej-102	83	51	for	for	ADP
alkej-102	83	52	lh	lh	PROPN
alkej-102	83	53	,	,	PUNCT
alkej-102	83	54	hl	hl	PROPN
alkej-102	83	55	,	,	PUNCT
alkej-102	83	56	hh	hh	PROPN
alkej-102	83	57	subbands	subband	NOUN
alkej-102	83	58	,	,	PUNCT
alkej-102	83	59	so	so	ADV
alkej-102	83	60	it	it	PRON
alkej-102	83	61	offered	offer	VERB
alkej-102	83	62	superior	superior	ADJ
alkej-102	83	63	results	result	NOUN
alkej-102	83	64	in	in	ADP
alkej-102	83	65	denoising	denoise	VERB
alkej-102	83	66	.	.	PUNCT
alkej-102	84	1	soft	soft	ADJ
alkej-102	84	2	thresholding	thresholding	NOUN
alkej-102	84	3	deletes	delete	VERB
alkej-102	84	4	the	the	DET
alkej-102	84	5	coefficients	coefficient	NOUN
alkej-102	84	6	under	under	ADP
alkej-102	84	7	the	the	DET
alkej-102	84	8	threshold	threshold	NOUN
alkej-102	84	9	,	,	PUNCT
alkej-102	84	10	but	but	CCONJ
alkej-102	84	11	scales	scale	VERB
alkej-102	84	12	the	the	DET
alkej-102	84	13	ones	one	NOUN
alkej-102	84	14	that	that	PRON
alkej-102	84	15	are	be	AUX
alkej-102	84	16	left	leave	VERB
alkej-102	84	17	.	.	PUNCT
alkej-102	85	1	there	there	PRON
alkej-102	85	2	are	be	VERB
alkej-102	85	3	different	different	ADJ
alkej-102	85	4	ways	way	NOUN
alkej-102	85	5	of	of	ADP
alkej-102	85	6	scaling	scaling	NOUN
alkej-102	85	7	.	.	PUNCT
alkej-102	86	1	the	the	DET
alkej-102	86	2	general	general	ADJ
alkej-102	86	3	soft	soft	ADJ
alkej-102	86	4	shrinkage	shrinkage	NOUN
alkej-102	86	5	rule	rule	NOUN
alkej-102	86	6	is	be	AUX
alkej-102	86	7	defined	define	VERB
alkej-102	86	8	by	by	ADP
alkej-102	86	9	:	:	PUNCT
alkej-102	86	10			NUM
alkej-102	86	11	)	)	PUNCT
alkej-102	86	12	)	)	PUNCT
alkej-102	86	13	(	(	PUNCT
alkej-102	86	14	sgn	sgn	NOUN
alkej-102	86	15	(	(	PUNCT
alkej-102	86	16	)	)	PUNCT
alkej-102	86	17	(	(	PUNCT
alkej-102	86	18			VERB
alkej-102	86	19	www	www	PROPN
alkej-102	86	20	...	...	PUNCT
alkej-102	86	21	(	(	PUNCT
alkej-102	86	22	15	15	NUM
alkej-102	86	23	)	)	PUNCT
alkej-102	86	24	where	where	SCONJ
alkej-102	86	25			ADJ
alkej-102	86	26	is	be	AUX
alkej-102	86	27	the	the	DET
alkej-102	86	28	threshold	threshold	NOUN
alkej-102	86	29	and	and	CCONJ
alkej-102	86	30	the	the	DET
alkej-102	86	31	plus	plus	ADJ
alkej-102	86	32	sign	sign	NOUN
alkej-102	86	33	indicates	indicate	VERB
alkej-102	86	34	only	only	ADV
alkej-102	86	35	the	the	DET
alkej-102	86	36	coefficients	coefficient	NOUN
alkej-102	86	37	that	that	PRON
alkej-102	86	38	are	be	AUX
alkej-102	86	39	above	above	ADP
alkej-102	86	40	the	the	DET
alkej-102	86	41	threshold	threshold	NOUN
alkej-102	86	42	are	be	AUX
alkej-102	86	43	considered	consider	VERB
alkej-102	86	44	.	.	PUNCT
alkej-102	87	1	the	the	DET
alkej-102	87	2	proposed	propose	VERB
alkej-102	87	3	algorithm	algorithm	NOUN
alkej-102	87	4	is	be	AUX
alkej-102	87	5	described	describe	VERB
alkej-102	87	6	in	in	ADP
alkej-102	87	7	this	this	DET
alkej-102	87	8	section	section	NOUN
alkej-102	87	9	;	;	PUNCT
alkej-102	87	10	it	it	PRON
alkej-102	87	11	is	be	AUX
alkej-102	87	12	applied	apply	VERB
alkej-102	87	13	for	for	ADP
alkej-102	87	14	each	each	DET
alkej-102	87	15	(	(	PUNCT
alkej-102	87	16	red	red	ADJ
alkej-102	87	17	,	,	PUNCT
alkej-102	87	18	green	green	ADJ
alkej-102	87	19	,	,	PUNCT
alkej-102	87	20	and	and	CCONJ
alkej-102	87	21	blue	blue	ADJ
alkej-102	87	22	)	)	PUNCT
alkej-102	87	23	band	band	NOUN
alkej-102	87	24	separately	separately	ADV
alkej-102	87	25	.	.	PUNCT
alkej-102	88	1	iman	iman	PROPN
alkej-102	88	2	m.g	m.g	PROPN
alkej-102	88	3	.	.	PROPN
alkej-102	88	4	alwan	alwan	PROPN
alkej-102	88	5	al	al	PROPN
alkej-102	88	6	-	-	PUNCT
alkej-102	88	7	khwarizmi	khwarizmi	PROPN
alkej-102	88	8	engineering	engineering	NOUN
alkej-102	88	9	journal	journal	PROPN
alkej-102	88	10	,	,	PUNCT
alkej-102	88	11	vol	vol	NOUN
alkej-102	88	12	.	.	PROPN
alkej-102	88	13	8	8	NUM
alkej-102	88	14	,	,	PUNCT
alkej-102	88	15	no	no	INTJ
alkej-102	88	16	.	.	PUNCT
alkej-102	89	1	1,pp	1,pp	NUM
alkej-102	89	2	18	18	NUM
alkej-102	89	3	26	26	NUM
alkej-102	89	4	(	(	PUNCT
alkej-102	89	5	2012	2012	NUM
alkej-102	89	6	)	)	PUNCT
alkej-102	89	7	21	21	NUM
alkej-102	89	8	it	it	PRON
alkej-102	89	9	consists	consist	VERB
alkej-102	89	10	of	of	ADP
alkej-102	89	11	the	the	DET
alkej-102	89	12	following	follow	VERB
alkej-102	89	13	steps	step	NOUN
alkej-102	89	14	:	:	PUNCT
alkej-102	89	15	1read	1read	NUM
alkej-102	89	16	the	the	DET
alkej-102	89	17	noisy	noisy	ADJ
alkej-102	89	18	color	color	NOUN
alkej-102	89	19	image	image	NOUN
alkej-102	89	20	(	(	PUNCT
alkej-102	89	21	contaminated	contaminate	VERB
alkej-102	89	22	with	with	ADP
alkej-102	89	23	white	white	ADJ
alkej-102	89	24	gaussian	gaussian	PROPN
alkej-102	89	25	noise	noise	NOUN
alkej-102	89	26	)	)	PUNCT
alkej-102	90	1	2for	2for	ADP
alkej-102	90	2	each	each	PRON
alkej-102	90	3	(	(	PUNCT
alkej-102	90	4	r	r	NOUN
alkej-102	90	5	,	,	PUNCT
alkej-102	90	6	g	g	NOUN
alkej-102	90	7	,	,	PUNCT
alkej-102	90	8	b	b	NOUN
alkej-102	90	9	)	)	PUNCT
alkej-102	90	10	band	band	NOUN
alkej-102	90	11	apply	apply	VERB
alkej-102	90	12	swt	swt	PROPN
alkej-102	90	13	(	(	PUNCT
alkej-102	90	14	one	one	NUM
alkej-102	90	15	level	level	NOUN
alkej-102	90	16	of	of	ADP
alkej-102	90	17	decomposition	decomposition	NOUN
alkej-102	90	18	)	)	PUNCT
alkej-102	90	19	estimate	estimate	VERB
alkej-102	90	20	the	the	DET
alkej-102	90	21	noise	noise	NOUN
alkej-102	90	22	variance	variance	NOUN
alkej-102	90	23	in	in	ADP
alkej-102	90	24	the	the	DET
alkej-102	90	25	noisy	noisy	ADJ
alkej-102	90	26	image	image	NOUN
alkej-102	90	27	using	use	VERB
alkej-102	90	28	equation	equation	NOUN
alkej-102	90	29	(	(	PUNCT
alkej-102	90	30	14	14	NUM
alkej-102	90	31	)	)	PUNCT
alkej-102	90	32	calculate	calculate	VERB
alkej-102	90	33	the	the	DET
alkej-102	90	34	scale	scale	NOUN
alkej-102	90	35	parameter	parameter	NOUN
alkej-102	90	36			PROPN
alkej-102	90	37	using	use	VERB
alkej-102	90	38	equation	equation	NOUN
alkej-102	90	39	(	(	PUNCT
alkej-102	90	40	13	13	NUM
alkej-102	90	41	)	)	PUNCT
alkej-102	90	42	.	.	PUNCT
alkej-102	91	1	for	for	ADP
alkej-102	91	2	each	each	DET
alkej-102	91	3	detail	detail	NOUN
alkej-102	91	4	subband	subband	NOUN
alkej-102	91	5	,	,	PUNCT
alkej-102	91	6	compute	compute	VERB
alkej-102	91	7	the	the	DET
alkej-102	91	8	standard	standard	ADJ
alkej-102	91	9	deviation	deviation	NOUN
alkej-102	91	10	and	and	CCONJ
alkej-102	91	11	threshold	threshold	NOUN
alkej-102	91	12	nst	nst	ADP
alkej-102	91	13	using	use	VERB
alkej-102	91	14	equation	equation	NOUN
alkej-102	91	15	(	(	PUNCT
alkej-102	91	16	12	12	NUM
alkej-102	91	17	)	)	PUNCT
alkej-102	91	18	.	.	PUNCT
alkej-102	92	1	apply	apply	VERB
alkej-102	92	2	soft	soft	ADJ
alkej-102	92	3	threshold	threshold	NOUN
alkej-102	92	4	to	to	ADP
alkej-102	92	5	the	the	DET
alkej-102	92	6	subbands	subband	NOUN
alkej-102	92	7	lh1	lh1	PROPN
alkej-102	92	8	,	,	PUNCT
alkej-102	92	9	hl1	hl1	PROPN
alkej-102	92	10	,	,	PUNCT
alkej-102	92	11	hh1	hh1	ADV
alkej-102	92	12	.	.	PUNCT
alkej-102	93	1	3reconstruct	3reconstruct	NUM
alkej-102	93	2	a	a	DET
alkej-102	93	3	new	new	ADJ
alkej-102	93	4	image	image	NOUN
alkej-102	93	5	from	from	ADP
alkej-102	93	6	ll1	ll1	ADV
alkej-102	93	7	subband	subband	NOUN
alkej-102	93	8	only	only	ADV
alkej-102	93	9	while	while	SCONJ
alkej-102	93	10	making	make	VERB
alkej-102	93	11	other	other	ADJ
alkej-102	93	12	subbands	subband	NOUN
alkej-102	93	13	equal	equal	ADJ
alkej-102	93	14	to	to	ADP
alkej-102	93	15	zero	zero	NUM
alkej-102	93	16	,	,	PUNCT
alkej-102	93	17	by	by	ADP
alkej-102	93	18	applying	apply	VERB
alkej-102	93	19	inverse	inverse	NOUN
alkej-102	93	20	stationary	stationary	ADJ
alkej-102	93	21	wavelet	wavelet	NOUN
alkej-102	93	22	transform	transform	NOUN
alkej-102	93	23	.	.	PUNCT
alkej-102	94	1	4apply	4apply	NUM
alkej-102	94	2	an	an	DET
alkej-102	94	3	adaptive	adaptive	ADJ
alkej-102	94	4	wiener	wiener	NOUN
alkej-102	94	5	filter	filter	NOUN
alkej-102	94	6	to	to	ADP
alkej-102	94	7	the	the	DET
alkej-102	94	8	reconstructed	reconstructed	ADJ
alkej-102	94	9	image	image	NOUN
alkej-102	94	10	in	in	ADP
alkej-102	94	11	spatial	spatial	ADJ
alkej-102	94	12	domain	domain	NOUN
alkej-102	94	13	.	.	PUNCT
alkej-102	95	1	5reapplying	5reapplye	VERB
alkej-102	95	2	swt	swt	PROPN
alkej-102	95	3	to	to	ADP
alkej-102	95	4	the	the	DET
alkej-102	95	5	resultant	resultant	NOUN
alkej-102	95	6	image	image	NOUN
alkej-102	95	7	of	of	ADP
alkej-102	95	8	step	step	NOUN
alkej-102	95	9	4	4	NUM
alkej-102	95	10	.	.	PUNCT
alkej-102	96	1	6extract	6extract	NUM
alkej-102	96	2	the	the	DET
alkej-102	96	3	approximation	approximation	NOUN
alkej-102	96	4	subband	subband	NOUN
alkej-102	96	5	from	from	ADP
alkej-102	96	6	step	step	NOUN
alkej-102	96	7	5	5	NUM
alkej-102	96	8	denoted	denote	VERB
alkej-102	96	9	by	by	ADP
alkej-102	96	10	ll2	ll2	NOUN
alkej-102	96	11	,	,	PUNCT
alkej-102	96	12	then	then	ADV
alkej-102	96	13	grouping	group	VERB
alkej-102	96	14	it	it	PRON
alkej-102	96	15	with	with	ADP
alkej-102	96	16	the	the	DET
alkej-102	96	17	thresholded	thresholde	VERB
alkej-102	96	18	subbands	subband	NOUN
alkej-102	96	19	denoted	denote	VERB
alkej-102	96	20	by	by	ADP
alkej-102	96	21	(	(	PUNCT
alkej-102	96	22	^	^	PUNCT
alkej-102	96	23	lh	lh	PROPN
alkej-102	96	24	,	,	PUNCT
alkej-102	96	25	^	^	PUNCT
alkej-102	96	26	hl	hl	NOUN
alkej-102	96	27	,	,	PUNCT
alkej-102	96	28	and	and	CCONJ
alkej-102	96	29	^	^	PUNCT
alkej-102	96	30	hh	hh	PROPN
alkej-102	96	31	)	)	PUNCT
alkej-102	96	32	of	of	ADP
alkej-102	96	33	step	step	NOUN
alkej-102	96	34	2	2	NUM
alkej-102	96	35	as	as	ADP
alkej-102	96	36	ll	ll	PRON
alkej-102	96	37	,	,	PUNCT
alkej-102	96	38	lh	lh	PROPN
alkej-102	96	39	,	,	PUNCT
alkej-102	96	40	hl	hl	NOUN
alkej-102	96	41	,	,	PUNCT
alkej-102	96	42	and	and	CCONJ
alkej-102	96	43	hh	hh	PROPN
alkej-102	96	44	subbands	subband	NOUN
alkej-102	96	45	.	.	PUNCT
alkej-102	97	1	7apply	7apply	NUM
alkej-102	97	2	inverse	inverse	ADJ
alkej-102	97	3	stationary	stationary	ADJ
alkej-102	97	4	wavelet	wavelet	NOUN
alkej-102	97	5	transform	transform	NOUN
alkej-102	97	6	,	,	PUNCT
alkej-102	97	7	to	to	PART
alkej-102	97	8	get	get	VERB
alkej-102	97	9	the	the	DET
alkej-102	97	10	denoised	denoise	VERB
alkej-102	97	11	image	image	NOUN
alkej-102	97	12	.	.	PUNCT
alkej-102	98	1	figure	figure	NOUN
alkej-102	98	2	(	(	PUNCT
alkej-102	98	3	1	1	X
alkej-102	98	4	)	)	PUNCT
alkej-102	98	5	shows	show	VERB
alkej-102	98	6	the	the	DET
alkej-102	98	7	schematic	schematic	ADJ
alkej-102	98	8	of	of	ADP
alkej-102	98	9	this	this	DET
alkej-102	98	10	approach	approach	NOUN
alkej-102	98	11	fig.1	fig.1	PROPN
alkej-102	98	12	.	.	PUNCT
alkej-102	99	1	a	a	DET
alkej-102	99	2	schematic	schematic	ADJ
alkej-102	99	3	of	of	ADP
alkej-102	99	4	the	the	DET
alkej-102	99	5	proposed	propose	VERB
alkej-102	99	6	denoising	denoising	NOUN
alkej-102	99	7	algorithm	algorithm	NOUN
alkej-102	99	8	.	.	PUNCT
alkej-102	100	1	4	4	X
alkej-102	100	2	.	.	X
alkej-102	100	3	experimental	experimental	ADJ
alkej-102	100	4	results	result	NOUN
alkej-102	100	5	the	the	DET
alkej-102	100	6	experimental	experimental	ADJ
alkej-102	100	7	evaluation	evaluation	NOUN
alkej-102	100	8	is	be	AUX
alkej-102	100	9	performed	perform	VERB
alkej-102	100	10	on	on	ADP
alkej-102	100	11	color	color	NOUN
alkej-102	100	12	images	image	NOUN
alkej-102	100	13	of	of	ADP
alkej-102	100	14	size	size	NOUN
alkej-102	100	15	256	256	NUM
alkej-102	100	16	*	*	SYM
alkej-102	100	17	256	256	NUM
alkej-102	100	18	pixels	pixel	NOUN
alkej-102	100	19	at	at	ADP
alkej-102	100	20	different	different	ADJ
alkej-102	100	21	white	white	ADJ
alkej-102	100	22	gaussian	gaussian	PROPN
alkej-102	100	23	noise	noise	NOUN
alkej-102	100	24	levels	level	NOUN
alkej-102	100	25	shown	show	VERB
alkej-102	100	26	in	in	ADP
alkej-102	100	27	figure	figure	NOUN
alkej-102	100	28	(	(	PUNCT
alkej-102	100	29	2	2	NUM
alkej-102	100	30	)	)	PUNCT
alkej-102	100	31	.	.	PUNCT
alkej-102	101	1	the	the	DET
alkej-102	101	2	objective	objective	ADJ
alkej-102	101	3	quality	quality	NOUN
alkej-102	101	4	of	of	ADP
alkej-102	101	5	the	the	DET
alkej-102	101	6	reconstructed	reconstructed	ADJ
alkej-102	101	7	image	image	NOUN
alkej-102	101	8	is	be	AUX
alkej-102	101	9	in	in	ADP
alkej-102	101	10	terms	term	NOUN
alkej-102	101	11	of	of	ADP
alkej-102	101	12	the	the	DET
alkej-102	101	13	psnr	psnr	NOUN
alkej-102	101	14	of	of	ADP
alkej-102	101	15	the	the	DET
alkej-102	101	16	three	three	NUM
alkej-102	101	17	color	color	NOUN
alkej-102	101	18	components	component	NOUN
alkej-102	101	19	)	)	PUNCT
alkej-102	101	20	,	,	PUNCT
alkej-102	101	21	,	,	PUNCT
alkej-102	101	22	{	{	PUNCT
alkej-102	101	23	,	,	PUNCT
alkej-102	101	24	bgrxx	bgrxx	VERB
alkej-102	101	25			NOUN
alkej-102	101	26	,	,	PUNCT
alkej-102	101	27	which	which	PRON
alkej-102	101	28	is	be	AUX
alkej-102	101	29	defined	define	VERB
alkej-102	101	30	as	as	ADP
alkej-102	101	31	[	[	X
alkej-102	101	32	9	9	NUM
alkej-102	101	33	]	]	NUM
alkej-102	101	34	:	:	PUNCT
alkej-102	101	35	)	)	PUNCT
alkej-102	101	36	(	(	PUNCT
alkej-102	101	37	255	255	NUM
alkej-102	101	38	log10	log10	PROPN
alkej-102	101	39	2	2	NUM
alkej-102	101	40	10	10	NUM
alkej-102	101	41	xmse	xmse	PROPN
alkej-102	101	42	psnr	psnr	PROPN
alkej-102	101	43			PROPN
alkej-102	101	44	...	...	PUNCT
alkej-102	101	45	(	(	PUNCT
alkej-102	101	46	16	16	NUM
alkej-102	101	47	)	)	PUNCT
alkej-102	101	48	where	where	SCONJ
alkej-102	101	49	mse	mse	X
alkej-102	101	50	(	(	PUNCT
alkej-102	101	51	x	x	X
alkej-102	101	52	)	)	PUNCT
alkej-102	101	53	is	be	AUX
alkej-102	101	54	the	the	DET
alkej-102	101	55	mean	mean	ADJ
alkej-102	101	56	-	-	PUNCT
alkej-102	101	57	square	square	ADJ
alkej-102	101	58	-	-	PUNCT
alkej-102	101	59	error	error	NOUN
alkej-102	101	60	of	of	ADP
alkej-102	101	61	the	the	DET
alkej-102	101	62	original	original	ADJ
alkej-102	101	63	color	color	NOUN
alkej-102	101	64	component	component	NOUN
alkej-102	101	65	and	and	CCONJ
alkej-102	101	66	the	the	DET
alkej-102	101	67	estimated	estimate	VERB
alkej-102	101	68	one	one	NUM
alkej-102	101	69	..	..	PUNCT
alkej-102	101	70	the	the	DET
alkej-102	101	71	overall	overall	ADJ
alkej-102	101	72	psnr	psnr	NOUN
alkej-102	101	73	is	be	AUX
alkej-102	101	74	obtained	obtain	VERB
alkej-102	101	75	as	as	ADP
alkej-102	101	76	)	)	PUNCT
alkej-102	101	77	(	(	PUNCT
alkej-102	101	78	)	)	PUNCT
alkej-102	101	79	(	(	PUNCT
alkej-102	101	80	)	)	PUNCT
alkej-102	101	81	(	(	PUNCT
alkej-102	101	82	255	255	NUM
alkej-102	101	83	log10	log10	PROPN
alkej-102	101	84	2	2	NUM
alkej-102	101	85	10	10	NUM
alkej-102	101	86	bmsegmsermse	bmsegmsermse	ADJ
alkej-102	101	87	psnr	psnr	NOUN
alkej-102	101	88			PROPN
alkej-102	101	89			PROPN
alkej-102	101	90	...	...	PUNCT
alkej-102	101	91	(	(	PUNCT
alkej-102	101	92	17	17	NUM
alkej-102	101	93	)	)	PUNCT
alkej-102	101	94	the	the	DET
alkej-102	101	95	proposed	propose	VERB
alkej-102	101	96	method	method	NOUN
alkej-102	101	97	was	be	AUX
alkej-102	101	98	implemented	implement	VERB
alkej-102	101	99	using	use	VERB
alkej-102	101	100	matalab	matalab	PROPN
alkej-102	101	101	r2010a	r2010a	PROPN
alkej-102	101	102	.	.	PUNCT
alkej-102	102	1	the	the	DET
alkej-102	102	2	psnr	psnr	NOUN
alkej-102	102	3	results	result	NOUN
alkej-102	102	4	are	be	AUX
alkej-102	102	5	shown	show	VERB
alkej-102	102	6	in	in	ADP
alkej-102	102	7	table	table	NOUN
alkej-102	102	8	(	(	PUNCT
alkej-102	102	9	1	1	NUM
alkej-102	102	10	)	)	PUNCT
alkej-102	102	11	.	.	PUNCT
alkej-102	103	1	swt	swt	PROPN
alkej-102	103	2	ll1	ll1	PROPN
alkej-102	103	3	lh1	lh1	PROPN
alkej-102	103	4	hl1	hl1	PROPN
alkej-102	103	5	hh1	hh1	VERB
alkej-102	103	6	lh	lh	PROPN
alkej-102	103	7	1	1	NUM
alkej-102	103	8	hl	hl	NOUN
alkej-102	103	9	1	1	NUM
alkej-102	103	10	hh	hh	NOUN
alkej-102	103	11	1	1	NUM
alkej-102	103	12	apply	apply	VERB
alkej-102	103	13	soft	soft	ADJ
alkej-102	103	14	threshold	threshold	NOUN
alkej-102	103	15	ll	ll	NOUN
alkej-102	103	16	1	1	NUM
alkej-102	103	17	iswt	iswt	NOUN
alkej-102	103	18	wiener	wiener	NOUN
alkej-102	103	19	filter	filter	NOUN
alkej-102	103	20	swt	swt	PROPN
alkej-102	103	21	ll2	ll2	PROPN
alkej-102	103	22	lh2	lh2	VERB
alkej-102	103	23	hl2	hl2	PROPN
alkej-102	103	24	hh2	hh2	NOUN
alkej-102	103	25	iswt	iswt	PROPN
alkej-102	103	26	denoised	denoise	VERB
alkej-102	103	27	image	image	NOUN
alkej-102	103	28	noisy	noisy	ADJ
alkej-102	103	29	image	image	NOUN
alkej-102	103	30	taking	take	VERB
alkej-102	103	31	ll	ll	NOUN
alkej-102	103	32	from	from	ADP
alkej-102	103	33	step	step	NOUN
alkej-102	103	34	2	2	NUM
alkej-102	103	35	while	while	SCONJ
alkej-102	103	36	other	other	ADJ
alkej-102	103	37	parts	part	NOUN
alkej-102	103	38	equal	equal	ADJ
alkej-102	103	39	to	to	ADP
alkej-102	103	40	zero	zero	NUM
alkej-102	103	41	output	output	NOUN
alkej-102	103	42	of	of	ADP
alkej-102	103	43	swt	swt	PROPN
alkej-102	103	44	(	(	PUNCT
alkej-102	103	45	2nx2n	2nx2n	NUM
alkej-102	103	46	)	)	PUNCT
alkej-102	103	47	for	for	ADP
alkej-102	103	48	nxn	nxn	PROPN
alkej-102	103	49	input	input	NOUN
alkej-102	103	50	image	image	NOUN
alkej-102	103	51	ll2	ll2	NOUN
alkej-102	103	52	^	^	PUNCT
alkej-102	103	53	lh	lh	PROPN
alkej-102	103	54	^	^	PUNCT
alkej-102	103	55	hl	hl	PROPN
alkej-102	103	56	^	^	PUNCT
alkej-102	103	57	hh	hh	PROPN
alkej-102	103	58	taking	take	VERB
alkej-102	103	59	ll2	ll2	NOUN
alkej-102	103	60	subband	subband	VERB
alkej-102	103	61	only	only	ADV
alkej-102	103	62	iman	iman	PROPN
alkej-102	103	63	m.g	m.g	PROPN
alkej-102	103	64	.	.	PROPN
alkej-102	103	65	alwan	alwan	PROPN
alkej-102	103	66	al	al	PROPN
alkej-102	103	67	-	-	PUNCT
alkej-102	103	68	khwarizmi	khwarizmi	PROPN
alkej-102	103	69	engineering	engineering	NOUN
alkej-102	103	70	journal	journal	PROPN
alkej-102	103	71	,	,	PUNCT
alkej-102	103	72	vol	vol	NOUN
alkej-102	103	73	.	.	PROPN
alkej-102	103	74	8	8	NUM
alkej-102	103	75	,	,	PUNCT
alkej-102	103	76	no	no	INTJ
alkej-102	103	77	.	.	PUNCT
alkej-102	104	1	1,pp	1,pp	NUM
alkej-102	104	2	18	18	NUM
alkej-102	104	3	26	26	NUM
alkej-102	104	4	(	(	PUNCT
alkej-102	104	5	2012	2012	NUM
alkej-102	104	6	)	)	PUNCT
alkej-102	104	7	22	22	NUM
alkej-102	104	8	fig.2	fig.2	PROPN
alkej-102	104	9	.	.	PUNCT
alkej-102	105	1	test	test	NOUN
alkej-102	105	2	color	color	NOUN
alkej-102	105	3	images	image	NOUN
alkej-102	105	4	.	.	PUNCT
alkej-102	106	1	table	table	NOUN
alkej-102	106	2	1	1	NUM
alkej-102	106	3	,	,	PUNCT
alkej-102	106	4	psnr	psnr	NOUN
alkej-102	106	5	of	of	ADP
alkej-102	106	6	various	various	ADJ
alkej-102	106	7	noisy	noisy	ADJ
alkej-102	106	8	color	color	NOUN
alkej-102	106	9	images	image	NOUN
alkej-102	106	10	and	and	CCONJ
alkej-102	106	11	denoised	denoise	VERB
alkej-102	106	12	ones	one	NOUN
alkej-102	106	13	for	for	ADP
alkej-102	106	14	swt	swt	PROPN
alkej-102	106	15	,	,	PUNCT
alkej-102	106	16	wiener	wiener	NOUN
alkej-102	106	17	,	,	PUNCT
alkej-102	106	18	and	and	CCONJ
alkej-102	106	19	the	the	DET
alkej-102	106	20	proposed	propose	VERB
alkej-102	106	21	algorithm	algorithm	NOUN
alkej-102	106	22	.	.	PUNCT
alkej-102	107	1	test	test	NOUN
alkej-102	107	2	images	image	NOUN
alkej-102	107	3	noise	noise	NOUN
alkej-102	107	4	variance	variance	NOUN
alkej-102	107	5	noisy	noisy	ADJ
alkej-102	107	6	image	image	NOUN
alkej-102	107	7	psnr	psnr	NOUN
alkej-102	107	8	(	(	PUNCT
alkej-102	107	9	db	db	PROPN
alkej-102	107	10	)	)	PUNCT
alkej-102	107	11	swt	swt	PROPN
alkej-102	107	12	psnr	psnr	PROPN
alkej-102	107	13	(	(	PUNCT
alkej-102	107	14	db	db	PROPN
alkej-102	107	15	)	)	PUNCT
alkej-102	107	16	wiener	wiener	NOUN
alkej-102	107	17	psnr	psnr	NOUN
alkej-102	107	18	(	(	PUNCT
alkej-102	107	19	db	db	PROPN
alkej-102	107	20	)	)	PUNCT
alkej-102	107	21	proposed	propose	VERB
alkej-102	107	22	method	method	PROPN
alkej-102	107	23	psnr	psnr	NOUN
alkej-102	107	24	(	(	PUNCT
alkej-102	107	25	db	db	PROPN
alkej-102	107	26	)	)	PUNCT
alkej-102	107	27	baboon	baboon	NOUN
alkej-102	107	28	0.003	0.003	NUM
alkej-102	107	29	30.06	30.06	NUM
alkej-102	107	30	32.53	32.53	NUM
alkej-102	107	31	32.83	32.83	NUM
alkej-102	107	32	30.28	30.28	NUM
alkej-102	107	33	0.007	0.007	NUM
alkej-102	107	34	26.43	26.43	NUM
alkej-102	107	35	30.84	30.84	NUM
alkej-102	107	36	31.19	31.19	NUM
alkej-102	107	37	29.95	29.95	NUM
alkej-102	107	38	0.010	0.010	NUM
alkej-102	107	39	24.92	24.92	NUM
alkej-102	107	40	29.95	29.95	NUM
alkej-102	107	41	30.27	30.27	NUM
alkej-102	107	42	29.76	29.76	NUM
alkej-102	107	43	0.030	0.030	NUM
alkej-102	107	44	20.38	20.38	NUM
alkej-102	107	45	26.57	26.57	NUM
alkej-102	107	46	26.81	26.81	NUM
alkej-102	107	47	28.64	28.64	NUM
alkej-102	107	48	0.060	0.060	NUM
alkej-102	107	49	17.79	17.79	NUM
alkej-102	107	50	24.26	24.26	NUM
alkej-102	107	51	24.81	24.81	NUM
alkej-102	107	52	27.29	27.29	NUM
alkej-102	107	53	0.080	0.080	NUM
alkej-102	107	54	16.82	16.82	NUM
alkej-102	107	55	23.30	23.30	NUM
alkej-102	107	56	23.72	23.72	NUM
alkej-102	107	57	26.65	26.65	NUM
alkej-102	107	58	0.100	0.100	NUM
alkej-102	107	59	16.17	16.17	NUM
alkej-102	107	60	22.67	22.67	NUM
alkej-102	107	61	23.08	23.08	NUM
alkej-102	107	62	26.07	26.07	NUM
alkej-102	107	63	airplane	airplane	NOUN
alkej-102	107	64	0.003	0.003	NUM
alkej-102	107	65	30.01	30.01	NUM
alkej-102	107	66	34.91	34.91	NUM
alkej-102	107	67	35.71	35.71	NUM
alkej-102	107	68	33.14	33.14	NUM
alkej-102	107	69	0.007	0.007	NUM
alkej-102	107	70	26.42	26.42	NUM
alkej-102	107	71	32.21	32.21	NUM
alkej-102	107	72	33.09	33.09	NUM
alkej-102	107	73	32.43	32.43	NUM
alkej-102	107	74	0.010	0.010	NUM
alkej-102	107	75	24.93	24.93	NUM
alkej-102	107	76	31.04	31.04	NUM
alkej-102	107	77	31.09	31.09	NUM
alkej-102	107	78	32.04	32.04	NUM
alkej-102	107	79	0.030	0.030	NUM
alkej-102	107	80	20.76	20.76	NUM
alkej-102	107	81	27.35	27.35	NUM
alkej-102	107	82	27.71	27.71	NUM
alkej-102	107	83	30.27	30.27	NUM
alkej-102	107	84	0.060	0.060	NUM
alkej-102	107	85	18.29	18.29	NUM
alkej-102	107	86	24.84	24.84	NUM
alkej-102	107	87	25.06	25.06	NUM
alkej-102	107	88	28.19	28.19	NUM
alkej-102	107	89	0.080	0.080	NUM
alkej-102	107	90	17.28	17.28	NUM
alkej-102	107	91	23.75	23.75	NUM
alkej-102	107	92	24.00	24.00	NUM
alkej-102	107	93	27.21	27.21	NUM
alkej-102	107	94	0.100	0.100	NUM
alkej-102	107	95	16.56	16.56	NUM
alkej-102	107	96	22.99	22.99	NUM
alkej-102	107	97	23.25	23.25	NUM
alkej-102	107	98	26.35	26.35	NUM
alkej-102	107	99	house	house	NOUN
alkej-102	107	100	0.003	0.003	NUM
alkej-102	107	101	30.01	30.01	NUM
alkej-102	107	102	34.46	34.46	NUM
alkej-102	107	103	35.55	35.55	NUM
alkej-102	107	104	34.06	34.06	NUM
alkej-102	107	105	0.007	0.007	NUM
alkej-102	107	106	26.38	26.38	NUM
alkej-102	107	107	32.21	32.21	NUM
alkej-102	107	108	32.94	32.94	NUM
alkej-102	107	109	33.11	33.11	NUM
alkej-102	107	110	0.010	0.010	NUM
alkej-102	107	111	24.88	24.88	NUM
alkej-102	107	112	31.04	31.04	NUM
alkej-102	107	113	31.70	31.70	NUM
alkej-102	107	114	32.63	32.63	NUM
alkej-102	107	115	0.030	0.030	NUM
alkej-102	107	116	20.44	20.44	NUM
alkej-102	107	117	27.35	27.35	NUM
alkej-102	107	118	27.44	27.44	NUM
alkej-102	107	119	30.48	30.48	NUM
alkej-102	107	120	0.060	0.060	NUM
alkej-102	107	121	17.86	17.86	NUM
alkej-102	107	122	24.84	24.84	NUM
alkej-102	107	123	24.97	24.97	NUM
alkej-102	107	124	28.64	28.64	NUM
alkej-102	107	125	0.080	0.080	NUM
alkej-102	107	126	16.90	16.90	NUM
alkej-102	107	127	23.75	23.75	NUM
alkej-102	107	128	24.00	24.00	NUM
alkej-102	107	129	27.70	27.70	NUM
alkej-102	107	130	0.100	0.100	NUM
alkej-102	107	131	16.20	16.20	NUM
alkej-102	107	132	22.99	22.99	NUM
alkej-102	107	133	23.31	23.31	NUM
alkej-102	107	134	26.95	26.95	NUM
alkej-102	107	135	lena	lena	PROPN
alkej-102	107	136	0.003	0.003	NUM
alkej-102	107	137	30.04	30.04	NUM
alkej-102	107	138	35.55	35.55	NUM
alkej-102	107	139	36.25	36.25	NUM
alkej-102	107	140	34.87	34.87	NUM
alkej-102	107	141	0.007	0.007	NUM
alkej-102	107	142	26.48	26.48	NUM
alkej-102	107	143	32.72	32.72	NUM
alkej-102	107	144	32.72	32.72	NUM
alkej-102	107	145	34.04	34.04	NUM
alkej-102	107	146	0.010	0.010	NUM
alkej-102	107	147	24.97	24.97	NUM
alkej-102	107	148	31.44	31.44	NUM
alkej-102	107	149	31.44	31.44	NUM
alkej-102	107	150	33.49	33.49	NUM
alkej-102	107	151	0.030	0.030	NUM
alkej-102	107	152	20.54	20.54	NUM
alkej-102	107	153	27.24	27.24	NUM
alkej-102	107	154	27.24	27.24	NUM
alkej-102	107	155	31.04	31.04	NUM
alkej-102	107	156	0.060	0.060	NUM
alkej-102	107	157	17.96	17.96	NUM
alkej-102	107	158	24.72	24.72	NUM
alkej-102	107	159	24.72	24.72	NUM
alkej-102	107	160	28.81	28.81	NUM
alkej-102	107	161	0.080	0.080	NUM
alkej-102	107	162	16.99	16.99	NUM
alkej-102	107	163	23.69	23.69	NUM
alkej-102	107	164	23.69	23.69	NUM
alkej-102	107	165	27.71	27.71	NUM
alkej-102	107	166	0.100	0.100	NUM
alkej-102	107	167	16.25	16.25	NUM
alkej-102	107	168	22.92	22.92	NUM
alkej-102	107	169	22.92	22.92	NUM
alkej-102	107	170	26.96	26.96	NUM
alkej-102	107	171	pepper	pepper	NOUN
alkej-102	107	172	0.003	0.003	NUM
alkej-102	107	173	30.14	30.14	NUM
alkej-102	107	174	35.50	35.50	NUM
alkej-102	107	175	36.44	36.44	NUM
alkej-102	107	176	34.82	34.82	NUM
alkej-102	107	177	0.007	0.007	NUM
alkej-102	107	178	26.57	26.57	NUM
alkej-102	107	179	32.63	32.63	NUM
alkej-102	107	180	32.63	32.63	NUM
alkej-102	107	181	33.67	33.67	NUM
alkej-102	107	182	0.010	0.010	NUM
alkej-102	107	183	25.05	25.05	NUM
alkej-102	107	184	31.26	31.26	NUM
alkej-102	107	185	31.26	31.26	NUM
alkej-102	107	186	33.07	33.07	NUM
alkej-102	107	187	iman	iman	PROPN
alkej-102	107	188	m.g	m.g	PROPN
alkej-102	107	189	.	.	PROPN
alkej-102	107	190	alwan	alwan	PROPN
alkej-102	107	191	al	al	PROPN
alkej-102	107	192	-	-	PUNCT
alkej-102	107	193	khwarizmi	khwarizmi	PROPN
alkej-102	107	194	engineering	engineering	NOUN
alkej-102	107	195	journal	journal	PROPN
alkej-102	107	196	,	,	PUNCT
alkej-102	107	197	vol	vol	NOUN
alkej-102	107	198	.	.	PROPN
alkej-102	107	199	8	8	NUM
alkej-102	107	200	,	,	PUNCT
alkej-102	107	201	no	no	INTJ
alkej-102	107	202	.	.	PUNCT
alkej-102	108	1	1,pp	1,pp	NUM
alkej-102	108	2	18	18	NUM
alkej-102	108	3	26	26	NUM
alkej-102	108	4	(	(	PUNCT
alkej-102	108	5	2012	2012	NUM
alkej-102	108	6	)	)	PUNCT
alkej-102	108	7	23	23	NUM
alkej-102	108	8	0.030	0.030	NUM
alkej-102	108	9	20.72	20.72	NUM
alkej-102	108	10	27.25	27.25	NUM
alkej-102	108	11	27.25	27.25	NUM
alkej-102	108	12	30.58	30.58	NUM
alkej-102	108	13	0.060	0.060	NUM
alkej-102	108	14	18.18	18.18	NUM
alkej-102	108	15	24.73	24.73	NUM
alkej-102	108	16	24.73	24.73	NUM
alkej-102	108	17	28.37	28.37	NUM
alkej-102	108	18	0.080	0.080	NUM
alkej-102	108	19	17.17	17.17	NUM
alkej-102	108	20	23.65	23.65	NUM
alkej-102	108	21	23.65	23.65	NUM
alkej-102	108	22	27.20	27.20	NUM
alkej-102	108	23	0.100	0.100	NUM
alkej-102	108	24	16.43	16.43	NUM
alkej-102	108	25	22.82	22.82	NUM
alkej-102	108	26	22.82	22.82	NUM
alkej-102	108	27	26.29	26.29	NUM
alkej-102	108	28	mona	mona	PROPN
alkej-102	108	29	liza	liza	PROPN
alkej-102	108	30	0.003	0.003	NUM
alkej-102	108	31	30.33	30.33	NUM
alkej-102	108	32	33.23	33.23	NUM
alkej-102	108	33	33.91	33.91	NUM
alkej-102	108	34	30.14	30.14	NUM
alkej-102	108	35	0.007	0.007	NUM
alkej-102	108	36	26.68	26.68	NUM
alkej-102	108	37	30.90	30.90	NUM
alkej-102	108	38	31.91	31.91	NUM
alkej-102	108	39	29.36	29.36	NUM
alkej-102	108	40	0.010	0.010	NUM
alkej-102	108	41	25.21	25.21	NUM
alkej-102	108	42	29.90	29.90	NUM
alkej-102	108	43	30.84	30.84	NUM
alkej-102	108	44	28.48	28.48	NUM
alkej-102	108	45	0.030	0.030	NUM
alkej-102	108	46	20.81	20.81	NUM
alkej-102	108	47	26.45	26.45	NUM
alkej-102	108	48	26.89	26.89	NUM
alkej-102	108	49	27.46	27.46	NUM
alkej-102	108	50	0.060	0.060	NUM
alkej-102	108	51	18.26	18.26	NUM
alkej-102	108	52	24.11	24.11	NUM
alkej-102	108	53	24.32	24.32	NUM
alkej-102	108	54	25.99	25.99	NUM
alkej-102	108	55	0.080	0.080	NUM
alkej-102	108	56	17.26	17.26	NUM
alkej-102	108	57	23.22	23.22	NUM
alkej-102	108	58	23.31	23.31	NUM
alkej-102	108	59	25.25	25.25	NUM
alkej-102	108	60	0.100	0.100	NUM
alkej-102	108	61	16.50	16.50	NUM
alkej-102	108	62	22.38	22.38	NUM
alkej-102	108	63	22.60	22.60	NUM
alkej-102	108	64	24.55	24.55	NUM
alkej-102	108	65	watch	watch	VERB
alkej-102	108	66	0.003	0.003	NUM
alkej-102	108	67	30.10	30.10	NUM
alkej-102	108	68	36.39	36.39	NUM
alkej-102	108	69	35.92	35.92	NUM
alkej-102	108	70	35.72	35.72	NUM
alkej-102	108	71	0.007	0.007	NUM
alkej-102	108	72	26.57	26.57	NUM
alkej-102	108	73	33.47	33.47	NUM
alkej-102	108	74	34.20	34.20	NUM
alkej-102	108	75	34.85	34.85	NUM
alkej-102	108	76	0.010	0.010	NUM
alkej-102	108	77	25.10	25.10	NUM
alkej-102	108	78	32.11	32.11	NUM
alkej-102	108	79	33.25	33.25	NUM
alkej-102	108	80	34.25	34.25	NUM
alkej-102	108	81	0.030	0.030	NUM
alkej-102	108	82	20.73	20.73	NUM
alkej-102	108	83	27.88	27.88	NUM
alkej-102	108	84	29.80	29.80	NUM
alkej-102	108	85	31.59	31.59	NUM
alkej-102	108	86	0.060	0.060	NUM
alkej-102	108	87	18.18	18.18	NUM
alkej-102	108	88	25.22	25.22	NUM
alkej-102	108	89	27.36	27.36	NUM
alkej-102	108	90	29.04	29.04	NUM
alkej-102	108	91	0.080	0.080	NUM
alkej-102	108	92	17.19	17.19	NUM
alkej-102	108	93	24.14	24.14	NUM
alkej-102	108	94	26.36	26.36	NUM
alkej-102	108	95	27.90	27.90	NUM
alkej-102	108	96	0.100	0.100	NUM
alkej-102	108	97	16.47	16.47	NUM
alkej-102	108	98	23.26	23.26	NUM
alkej-102	108	99	25.49	25.49	NUM
alkej-102	108	100	26.92	26.92	NUM
alkej-102	108	101	flower	flower	NOUN
alkej-102	108	102	0.003	0.003	NUM
alkej-102	108	103	30.24	30.24	NUM
alkej-102	108	104	35.67	35.67	NUM
alkej-102	108	105	35.33	35.33	NUM
alkej-102	108	106	34.59	34.59	NUM
alkej-102	108	107	0.007	0.007	NUM
alkej-102	108	108	26.66	26.66	NUM
alkej-102	108	109	33.01	33.01	NUM
alkej-102	108	110	33.60	33.60	NUM
alkej-102	108	111	33.69	33.69	NUM
alkej-102	108	112	0.010	0.010	NUM
alkej-102	108	113	25.17	25.17	NUM
alkej-102	108	114	31.79	31.79	NUM
alkej-102	108	115	32.65	32.65	NUM
alkej-102	108	116	33.19	33.19	NUM
alkej-102	108	117	0.030	0.030	NUM
alkej-102	108	118	20.68	20.68	NUM
alkej-102	108	119	27.57	27.57	NUM
alkej-102	108	120	29.18	29.18	NUM
alkej-102	108	121	30.64	30.64	NUM
alkej-102	108	122	0.060	0.060	NUM
alkej-102	108	123	18.11	18.11	NUM
alkej-102	108	124	24.91	24.91	NUM
alkej-102	108	125	26.77	26.77	NUM
alkej-102	108	126	28.39	28.39	NUM
alkej-102	108	127	0.080	0.080	NUM
alkej-102	108	128	17.12	17.12	NUM
alkej-102	108	129	23.89	23.89	NUM
alkej-102	108	130	25.90	25.90	NUM
alkej-102	108	131	27.33	27.33	NUM
alkej-102	108	132	0.100	0.100	NUM
alkej-102	108	133	16.40	16.40	NUM
alkej-102	108	134	23.07	23.07	NUM
alkej-102	108	135	25.11	25.11	NUM
alkej-102	108	136	26.47	26.47	NUM
alkej-102	108	137	from	from	ADP
alkej-102	108	138	the	the	DET
alkej-102	108	139	results	result	NOUN
alkej-102	108	140	we	we	PRON
alkej-102	108	141	can	can	AUX
alkej-102	108	142	find	find	VERB
alkej-102	108	143	that	that	SCONJ
alkej-102	108	144	the	the	DET
alkej-102	108	145	psnr	psnr	NOUN
alkej-102	108	146	of	of	ADP
alkej-102	108	147	the	the	DET
alkej-102	108	148	proposed	propose	VERB
alkej-102	108	149	method	method	NOUN
alkej-102	108	150	offers	offer	VERB
alkej-102	108	151	superior	superior	ADJ
alkej-102	108	152	improvement	improvement	NOUN
alkej-102	108	153	over	over	ADP
alkej-102	108	154	swt	swt	PROPN
alkej-102	108	155	based	base	VERB
alkej-102	108	156	method	method	NOUN
alkej-102	108	157	and	and	CCONJ
alkej-102	108	158	wiener	wiener	NOUN
alkej-102	108	159	filter	filter	NOUN
alkej-102	108	160	method	method	NOUN
alkej-102	108	161	at	at	ADP
alkej-102	108	162	middle	middle	ADJ
alkej-102	108	163	and	and	CCONJ
alkej-102	108	164	high	high	ADJ
alkej-102	108	165	values	value	NOUN
alkej-102	108	166	of	of	ADP
alkej-102	108	167	noise	noise	NOUN
alkej-102	108	168	with	with	ADP
alkej-102	108	169	smoothing	smooth	VERB
alkej-102	108	170	edges	edge	NOUN
alkej-102	108	171	of	of	ADP
alkej-102	108	172	the	the	DET
alkej-102	108	173	image	image	NOUN
alkej-102	108	174	.	.	PUNCT
alkej-102	109	1	at	at	ADP
alkej-102	109	2	low	low	ADJ
alkej-102	109	3	values	value	NOUN
alkej-102	109	4	of	of	ADP
alkej-102	109	5	noise	noise	NOUN
alkej-102	109	6	the	the	DET
alkej-102	109	7	proposed	propose	VERB
alkej-102	109	8	method	method	NOUN
alkej-102	109	9	offers	offer	VERB
alkej-102	109	10	poorer	poor	ADJ
alkej-102	109	11	response	response	NOUN
alkej-102	109	12	because	because	SCONJ
alkej-102	109	13	the	the	DET
alkej-102	109	14	levels	level	NOUN
alkej-102	109	15	of	of	ADP
alkej-102	109	16	noise	noise	NOUN
alkej-102	109	17	are	be	AUX
alkej-102	109	18	very	very	ADV
alkej-102	109	19	low	low	ADJ
alkej-102	109	20	at	at	ADP
alkej-102	109	21	low	low	ADJ
alkej-102	109	22	band	band	NOUN
alkej-102	109	23	frequencies	frequency	NOUN
alkej-102	109	24	so	so	SCONJ
alkej-102	109	25	the	the	DET
alkej-102	109	26	effect	effect	NOUN
alkej-102	109	27	of	of	ADP
alkej-102	109	28	wiener	wiener	NOUN
alkej-102	109	29	filtering	filtering	NOUN
alkej-102	109	30	for	for	ADP
alkej-102	109	31	the	the	DET
alkej-102	109	32	reconstructed	reconstruct	VERB
alkej-102	109	33	images	image	NOUN
alkej-102	109	34	from	from	ADP
alkej-102	109	35	ll	ll	PRON
alkej-102	109	36	subband	subband	NOUN
alkej-102	109	37	of	of	ADP
alkej-102	109	38	the	the	DET
alkej-102	109	39	swt	swt	PROPN
alkej-102	109	40	step	step	NOUN
alkej-102	109	41	is	be	AUX
alkej-102	109	42	not	not	PART
alkej-102	109	43	effective	effective	ADJ
alkej-102	109	44	.	.	PUNCT
alkej-102	110	1	at	at	ADP
alkej-102	110	2	middle	middle	ADJ
alkej-102	110	3	and	and	CCONJ
alkej-102	110	4	high	high	ADJ
alkej-102	110	5	levels	level	NOUN
alkej-102	110	6	of	of	ADP
alkej-102	110	7	noise	noise	NOUN
alkej-102	110	8	,	,	PUNCT
alkej-102	110	9	the	the	DET
alkej-102	110	10	ll	ll	NOUN
alkej-102	110	11	subband	subband	NOUN
alkej-102	110	12	of	of	ADP
alkej-102	110	13	swt	swt	PROPN
alkej-102	110	14	step	step	NOUN
alkej-102	110	15	is	be	AUX
alkej-102	110	16	more	more	ADV
alkej-102	110	17	attacked	attack	VERB
alkej-102	110	18	by	by	ADP
alkej-102	110	19	noise	noise	NOUN
alkej-102	110	20	values	value	NOUN
alkej-102	110	21	,	,	PUNCT
alkej-102	110	22	so	so	CCONJ
alkej-102	110	23	the	the	DET
alkej-102	110	24	effect	effect	NOUN
alkej-102	110	25	of	of	ADP
alkej-102	110	26	wiener	wiener	NOUN
alkej-102	110	27	filtering	filtering	NOUN
alkej-102	110	28	is	be	AUX
alkej-102	110	29	more	more	ADV
alkej-102	110	30	noticeable	noticeable	ADJ
alkej-102	110	31	.	.	PUNCT
alkej-102	111	1	figure	figure	NOUN
alkej-102	111	2	(	(	PUNCT
alkej-102	111	3	3	3	X
alkej-102	111	4	)	)	PUNCT
alkej-102	111	5	shows	show	VERB
alkej-102	111	6	the	the	DET
alkej-102	111	7	results	result	NOUN
alkej-102	111	8	of	of	ADP
alkej-102	111	9	each	each	DET
alkej-102	111	10	denoising	denoising	NOUN
alkej-102	111	11	method	method	NOUN
alkej-102	111	12	for	for	ADP
alkej-102	111	13	three	three	NUM
alkej-102	111	14	testing	testing	NOUN
alkej-102	111	15	images	image	NOUN
alkej-102	111	16	(	(	PUNCT
alkej-102	111	17	pepper	pepper	NOUN
alkej-102	111	18	,	,	PUNCT
alkej-102	111	19	airplane	airplane	NOUN
alkej-102	111	20	,	,	PUNCT
alkej-102	111	21	flower	flower	NOUN
alkej-102	111	22	)	)	PUNCT
alkej-102	111	23	for	for	ADP
alkej-102	111	24	noise	noise	NOUN
alkej-102	111	25	variance	variance	NOUN
alkej-102	111	26	(	(	PUNCT
alkej-102	111	27	0.1	0.1	NUM
alkej-102	111	28	,	,	PUNCT
alkej-102	111	29	0.06	0.06	NUM
alkej-102	111	30	.	.	NOUN
alkej-102	111	31	0.08	0.08	NUM
alkej-102	111	32	)	)	PUNCT
alkej-102	111	33	.	.	PUNCT
alkej-102	112	1	also	also	ADV
alkej-102	112	2	the	the	DET
alkej-102	112	3	results	result	NOUN
alkej-102	112	4	of	of	ADP
alkej-102	112	5	the	the	DET
alkej-102	112	6	proposed	propose	VERB
alkej-102	112	7	algorithm	algorithm	NOUN
alkej-102	112	8	,	,	PUNCT
alkej-102	112	9	for	for	ADP
alkej-102	112	10	gray	gray	ADJ
alkej-102	112	11	scale	scale	NOUN
alkej-102	112	12	images	image	NOUN
alkej-102	112	13	(	(	PUNCT
alkej-102	112	14	pepper	pepper	NOUN
alkej-102	112	15	and	and	CCONJ
alkej-102	112	16	house	house	NOUN
alkej-102	112	17	)	)	PUNCT
alkej-102	112	18	were	be	AUX
alkej-102	112	19	compared	compare	VERB
alkej-102	112	20	with	with	ADP
alkej-102	112	21	the	the	DET
alkej-102	112	22	results	result	NOUN
alkej-102	112	23	of	of	ADP
alkej-102	112	24	the	the	DET
alkej-102	112	25	proposed	propose	VERB
alkej-102	112	26	methods	method	NOUN
alkej-102	112	27	of	of	ADP
alkej-102	112	28	[	[	X
alkej-102	112	29	4	4	X
alkej-102	112	30	]	]	PUNCT
alkej-102	112	31	in	in	ADP
alkej-102	112	32	term	term	NOUN
alkej-102	112	33	of	of	ADP
alkej-102	112	34	snr	snr	PROPN
alkej-102	112	35	(	(	PUNCT
alkej-102	112	36	signal	signal	VERB
alkej-102	112	37	to	to	PART
alkej-102	112	38	noise	noise	VERB
alkej-102	112	39	ratio	ratio	NOUN
alkej-102	112	40	)	)	PUNCT
alkej-102	112	41	which	which	PRON
alkej-102	112	42	was	be	AUX
alkej-102	112	43	adopted	adopt	VERB
alkej-102	112	44	in	in	ADP
alkej-102	112	45	this	this	DET
alkej-102	112	46	paper	paper	NOUN
alkej-102	112	47	.	.	PUNCT
alkej-102	113	1			ADJ
alkej-102	113	2			ADP
alkej-102	113	3			NUM
alkej-102	113	4			NUM
alkej-102	113	5			X
alkej-102	113	6			NUM
alkej-102	113	7			NUM
alkej-102	113	8			NOUN
alkej-102	113	9			PROPN
alkej-102	113	10			NUM
alkej-102	113	11			NUM
alkej-102	113	12			PROPN
alkej-102	113	13			NUM
alkej-102	113	14			NUM
alkej-102	113	15			NUM
alkej-102	113	16			ADP
alkej-102	114	1			PROPN
alkej-102	114	2			PROPN
alkej-102	114	3			PRON
alkej-102	114	4			NOUN
alkej-102	114	5			VERB
alkej-102	114	6			PROPN
alkej-102	114	7			PROPN
alkej-102	114	8			PROPN
alkej-102	114	9			X
alkej-102	114	10			X
alkej-102	114	11	yx	yx	ADP
alkej-102	114	12	yx	yx	PROPN
alkej-102	114	13	yxxyxx	yxxyxx	PROPN
alkej-102	114	14	yxx	yxx	PROPN
alkej-102	114	15	snr	snr	PROPN
alkej-102	114	16	,	,	PUNCT
alkej-102	114	17	2	2	NUM
alkej-102	114	18	^	^	PUNCT
alkej-102	114	19	,	,	PUNCT
alkej-102	114	20	2	2	NUM
alkej-102	114	21	)	)	PUNCT
alkej-102	114	22	,	,	PUNCT
alkej-102	114	23	(	(	PUNCT
alkej-102	114	24	)	)	PUNCT
alkej-102	114	25	,	,	PUNCT
alkej-102	114	26	(	(	PUNCT
alkej-102	114	27	)	)	PUNCT
alkej-102	114	28	,	,	PUNCT
alkej-102	114	29	(	(	PUNCT
alkej-102	114	30	10log10	10log10	NUM
alkej-102	114	31	...	...	PUNCT
alkej-102	114	32	(	(	PUNCT
alkej-102	114	33	18	18	NUM
alkej-102	114	34	)	)	PUNCT
alkej-102	114	35	where	where	SCONJ
alkej-102	114	36	)	)	PUNCT
alkej-102	114	37	,	,	PUNCT
alkej-102	114	38	(	(	PUNCT
alkej-102	114	39	yxx	yxx	NOUN
alkej-102	114	40	and	and	CCONJ
alkej-102	114	41	)	)	PUNCT
alkej-102	114	42	,	,	PUNCT
alkej-102	114	43	(	(	PUNCT
alkej-102	114	44	^	^	SYM
alkej-102	114	45	yxx	yxx	PROPN
alkej-102	114	46	are	be	AUX
alkej-102	114	47	the	the	DET
alkej-102	114	48	original	original	ADJ
alkej-102	114	49	image	image	NOUN
alkej-102	114	50	and	and	CCONJ
alkej-102	114	51	denoised	denoise	VERB
alkej-102	114	52	image	image	NOUN
alkej-102	114	53	.	.	PUNCT
alkej-102	115	1	table	table	NOUN
alkej-102	115	2	(	(	PUNCT
alkej-102	115	3	2	2	X
alkej-102	115	4	)	)	PUNCT
alkej-102	115	5	shows	show	VERB
alkej-102	115	6	the	the	DET
alkej-102	115	7	comparison	comparison	NOUN
alkej-102	115	8	of	of	ADP
alkej-102	115	9	the	the	DET
alkej-102	115	10	proposed	propose	VERB
alkej-102	115	11	method	method	NOUN
alkej-102	115	12	with	with	ADP
alkej-102	115	13	results	result	NOUN
alkej-102	115	14	of	of	ADP
alkej-102	115	15	[	[	X
alkej-102	115	16	4	4	X
alkej-102	115	17	]	]	PUNCT
alkej-102	115	18	in	in	ADP
alkej-102	115	19	which	which	PRON
alkej-102	115	20	modified	modify	VERB
alkej-102	115	21	bayes	bayes	NOUN
alkej-102	115	22	shrink	shrink	NOUN
alkej-102	115	23	was	be	AUX
alkej-102	115	24	proposed	propose	VERB
alkej-102	115	25	.	.	PUNCT
alkej-102	116	1	from	from	ADP
alkej-102	116	2	the	the	DET
alkej-102	116	3	comparison	comparison	NOUN
alkej-102	116	4	table	table	NOUN
alkej-102	116	5	we	we	PRON
alkej-102	116	6	can	can	AUX
alkej-102	116	7	notice	notice	VERB
alkej-102	116	8	that	that	SCONJ
alkej-102	116	9	the	the	DET
alkej-102	116	10	results	result	NOUN
alkej-102	116	11	of	of	ADP
alkej-102	116	12	the	the	DET
alkej-102	116	13	proposed	propose	VERB
alkej-102	116	14	method	method	NOUN
alkej-102	116	15	are	be	AUX
alkej-102	116	16	slightly	slightly	ADV
alkej-102	116	17	better	well	ADJ
alkej-102	116	18	than	than	ADP
alkej-102	116	19	modified	modify	VERB
alkej-102	116	20	bs	b	NOUN
alkej-102	116	21	in	in	ADP
alkej-102	116	22	[	[	X
alkej-102	116	23	4	4	NUM
alkej-102	116	24	]	]	PUNCT
alkej-102	116	25	.	.	PUNCT
alkej-102	117	1	iman	iman	PROPN
alkej-102	117	2	m.g	m.g	PROPN
alkej-102	117	3	.	.	PROPN
alkej-102	117	4	alwan	alwan	PROPN
alkej-102	117	5	al	al	PROPN
alkej-102	117	6	-	-	PUNCT
alkej-102	117	7	khwarizmi	khwarizmi	PROPN
alkej-102	117	8	engineering	engineering	NOUN
alkej-102	117	9	journal	journal	PROPN
alkej-102	117	10	,	,	PUNCT
alkej-102	117	11	vol	vol	NOUN
alkej-102	117	12	.	.	PROPN
alkej-102	117	13	8	8	NUM
alkej-102	117	14	,	,	PUNCT
alkej-102	117	15	no	no	INTJ
alkej-102	117	16	.	.	PUNCT
alkej-102	118	1	1,pp	1,pp	NUM
alkej-102	118	2	18	18	NUM
alkej-102	118	3	26	26	NUM
alkej-102	118	4	(	(	PUNCT
alkej-102	118	5	2012	2012	NUM
alkej-102	118	6	)	)	PUNCT
alkej-102	118	7	24	24	NUM
alkej-102	118	8	noisy	noisy	ADJ
alkej-102	118	9	image	image	NOUN
alkej-102	118	10	,	,	PUNCT
alkej-102	118	11	variance=0.1	variance=0.1	PRON
alkej-102	118	12	denoised	denoise	VERB
alkej-102	118	13	(	(	PUNCT
alkej-102	118	14	proposed	propose	VERB
alkej-102	118	15	method	method	NOUN
alkej-102	118	16	)	)	PUNCT
alkej-102	118	17	denoised	denoise	VERB
alkej-102	118	18	(	(	PUNCT
alkej-102	118	19	wiener	wiener	NOUN
alkej-102	118	20	filter	filter	NOUN
alkej-102	118	21	)	)	PUNCT
alkej-102	118	22	denoised	denoise	VERB
alkej-102	118	23	(	(	PUNCT
alkej-102	118	24	swt	swt	NOUN
alkej-102	118	25	)	)	PUNCT
alkej-102	118	26	noisy	noisy	ADJ
alkej-102	118	27	image	image	NOUN
alkej-102	118	28	,	,	PUNCT
alkej-102	118	29	variance=0.08	variance=0.08	NOUN
alkej-102	118	30	denoised	denoise	VERB
alkej-102	118	31	(	(	PUNCT
alkej-102	118	32	proposed	propose	VERB
alkej-102	118	33	method	method	NOUN
alkej-102	118	34	)	)	PUNCT
alkej-102	118	35	denoised	denoise	VERB
alkej-102	118	36	(	(	PUNCT
alkej-102	118	37	wiener	wiener	NOUN
alkej-102	118	38	filter	filter	NOUN
alkej-102	118	39	)	)	PUNCT
alkej-102	118	40	denoised	denoise	VERB
alkej-102	118	41	(	(	PUNCT
alkej-102	118	42	swt	swt	PROPN
alkej-102	118	43	)	)	PUNCT
alkej-102	118	44	fig	fig	NOUN
alkej-102	118	45	.	.	PUNCT
alkej-102	119	1	3	3	X
alkej-102	119	2	.	.	X
alkej-102	119	3	results	result	NOUN
alkej-102	119	4	of	of	ADP
alkej-102	119	5	proposed	propose	VERB
alkej-102	119	6	,	,	PUNCT
alkej-102	119	7	wiener	wiener	NOUN
alkej-102	119	8	filter	filter	NOUN
alkej-102	119	9	,	,	PUNCT
alkej-102	119	10	and	and	CCONJ
alkej-102	119	11	swt	swt	PROPN
alkej-102	119	12	denoised	denoise	VERB
alkej-102	119	13	images	image	NOUN
alkej-102	119	14	.	.	PUNCT
alkej-102	120	1	table	table	NOUN
alkej-102	120	2	2	2	NUM
alkej-102	120	3	,	,	PUNCT
alkej-102	120	4	snr	snr	NOUN
alkej-102	120	5	of	of	ADP
alkej-102	120	6	the	the	DET
alkej-102	120	7	proposed	propose	VERB
alkej-102	120	8	method	method	NOUN
alkej-102	120	9	and	and	CCONJ
alkej-102	120	10	modified	modify	VERB
alkej-102	120	11	bs	b	NOUN
alkej-102	120	12	for	for	ADP
alkej-102	120	13	pepper	pepper	NOUN
alkej-102	120	14	and	and	CCONJ
alkej-102	120	15	house	house	PROPN
alkej-102	120	16	grey	grey	PROPN
alkej-102	120	17	images	image	NOUN
alkej-102	120	18	.	.	PUNCT
alkej-102	121	1	test	test	NOUN
alkej-102	121	2	images	image	NOUN
alkej-102	121	3	noise	noise	NOUN
alkej-102	121	4	variance	variance	NOUN
alkej-102	121	5	noisy	noisy	ADJ
alkej-102	121	6	image	image	NOUN
alkej-102	121	7	snr	snr	PROPN
alkej-102	121	8	proposed	propose	VERB
alkej-102	121	9	snr	snr	PROPN
alkej-102	121	10	modified	modify	VERB
alkej-102	121	11	bs	bs	PROPN
alkej-102	121	12	snr	snr	PROPN
alkej-102	121	13	pepper	pepper	VERB
alkej-102	121	14	0.01	0.01	NUM
alkej-102	121	15	14.55	14.55	NUM
alkej-102	121	16	22.49	22.49	NUM
alkej-102	121	17	21.21	21.21	NUM
alkej-102	121	18	0.03	0.03	NUM
alkej-102	121	19	10.08	10.08	NUM
alkej-102	121	20	20.36	20.36	NUM
alkej-102	121	21	18.76	18.76	NUM
alkej-102	121	22	0.06	0.06	NUM
alkej-102	121	23	8.15	8.15	NUM
alkej-102	121	24	18.38	18.38	NUM
alkej-102	121	25	17.51	17.51	NUM
alkej-102	121	26	house	house	NOUN
alkej-102	121	27	0.003	0.003	NUM
alkej-102	121	28	20.37	20.37	NUM
alkej-102	121	29	24.63	24.63	NUM
alkej-102	121	30	26.46	26.46	NUM
alkej-102	121	31	0.03	0.03	NUM
alkej-102	121	32	10.67	10.67	NUM
alkej-102	121	33	21.41	21.41	NUM
alkej-102	121	34	21.39	21.39	NUM
alkej-102	121	35	0.05	0.05	NUM
alkej-102	121	36	8.76	8.76	NUM
alkej-102	121	37	21.15	21.15	NUM
alkej-102	121	38	20.18	20.18	NUM
alkej-102	121	39	5	5	NUM
alkej-102	121	40	.	.	PUNCT
alkej-102	122	1	conclusion	conclusion	VERB
alkej-102	122	2	many	many	ADJ
alkej-102	122	3	methods	method	NOUN
alkej-102	122	4	of	of	ADP
alkej-102	122	5	denoising	denoise	VERB
alkej-102	122	6	algorithms	algorithm	NOUN
alkej-102	122	7	based	base	VERB
alkej-102	122	8	are	be	AUX
alkej-102	122	9	on	on	ADP
alkej-102	122	10	wiener	wiener	NOUN
alkej-102	122	11	filtering	filtering	NOUN
alkej-102	122	12	on	on	ADP
alkej-102	122	13	the	the	DET
alkej-102	122	14	wavelet	wavelet	NOUN
alkej-102	122	15	coefficients	coefficient	NOUN
alkej-102	122	16	.	.	PUNCT
alkej-102	123	1	in	in	ADP
alkej-102	123	2	this	this	DET
alkej-102	123	3	paper	paper	NOUN
alkej-102	123	4	a	a	DET
alkej-102	123	5	simple	simple	ADJ
alkej-102	123	6	and	and	CCONJ
alkej-102	123	7	efficient	efficient	ADJ
alkej-102	123	8	algorithm	algorithm	NOUN
alkej-102	123	9	for	for	ADP
alkej-102	123	10	adaptive	adaptive	ADJ
alkej-102	123	11	noise	noise	NOUN
alkej-102	123	12	reduction	reduction	NOUN
alkej-102	123	13	is	be	AUX
alkej-102	123	14	proposed	propose	VERB
alkej-102	123	15	,	,	PUNCT
alkej-102	123	16	it	it	PRON
alkej-102	123	17	combines	combine	VERB
alkej-102	123	18	the	the	DET
alkej-102	123	19	adaptive	adaptive	ADJ
alkej-102	123	20	wiener	wiener	NOUN
alkej-102	123	21	filter	filter	NOUN
alkej-102	123	22	in	in	ADP
alkej-102	123	23	spatial	spatial	ADJ
alkej-102	123	24	domain	domain	NOUN
alkej-102	123	25	and	and	CCONJ
alkej-102	123	26	thresholding	thresholding	NOUN
alkej-102	123	27	method	method	NOUN
alkej-102	123	28	in	in	ADP
alkej-102	123	29	the	the	DET
alkej-102	123	30	stationary	stationary	ADJ
alkej-102	123	31	wavelet	wavelet	NOUN
alkej-102	123	32	transform	transform	NOUN
alkej-102	123	33	domain	domain	NOUN
alkej-102	123	34	.	.	PUNCT
alkej-102	124	1	experimental	experimental	ADJ
alkej-102	124	2	results	result	NOUN
alkej-102	124	3	show	show	VERB
alkej-102	124	4	that	that	SCONJ
alkej-102	124	5	noisy	noisy	ADJ
alkej-102	124	6	image	image	NOUN
alkej-102	124	7	,	,	PUNCT
alkej-102	124	8	variance=0.06	variance=0.06	PROPN
alkej-102	124	9	denoised	denoise	VERB
alkej-102	124	10	(	(	PUNCT
alkej-102	124	11	proposed	propose	VERB
alkej-102	124	12	method	method	NOUN
alkej-102	124	13	)	)	PUNCT
alkej-102	124	14	denoised	denoise	VERB
alkej-102	124	15	(	(	PUNCT
alkej-102	124	16	wiener	wiener	NOUN
alkej-102	124	17	filter	filter	NOUN
alkej-102	124	18	)	)	PUNCT
alkej-102	124	19	denoised	denoise	VERB
alkej-102	124	20	(	(	PUNCT
alkej-102	124	21	swt	swt	PROPN
alkej-102	124	22	)	)	PUNCT
alkej-102	124	23	iman	iman	PROPN
alkej-102	124	24	m.g	m.g	PROPN
alkej-102	124	25	.	.	PROPN
alkej-102	124	26	alwan	alwan	PROPN
alkej-102	124	27	al	al	PROPN
alkej-102	124	28	-	-	PUNCT
alkej-102	124	29	khwarizmi	khwarizmi	PROPN
alkej-102	124	30	engineering	engineering	NOUN
alkej-102	124	31	journal	journal	PROPN
alkej-102	124	32	,	,	PUNCT
alkej-102	124	33	vol	vol	NOUN
alkej-102	124	34	.	.	PROPN
alkej-102	124	35	8	8	NUM
alkej-102	124	36	,	,	PUNCT
alkej-102	124	37	no	no	INTJ
alkej-102	124	38	.	.	PUNCT
alkej-102	125	1	1,pp	1,pp	NUM
alkej-102	125	2	18	18	NUM
alkej-102	125	3	26	26	NUM
alkej-102	125	4	(	(	PUNCT
alkej-102	125	5	2012	2012	NUM
alkej-102	125	6	)	)	PUNCT
alkej-102	125	7	25	25	NUM
alkej-102	125	8	the	the	DET
alkej-102	125	9	noise	noise	NOUN
alkej-102	125	10	reduction	reduction	NOUN
alkej-102	125	11	method	method	NOUN
alkej-102	125	12	exhibits	exhibit	VERB
alkej-102	125	13	better	well	ADJ
alkej-102	125	14	performance	performance	NOUN
alkej-102	125	15	in	in	ADP
alkej-102	125	16	both	both	CCONJ
alkej-102	125	17	psnr	psnr	NOUN
alkej-102	125	18	and	and	CCONJ
alkej-102	125	19	visual	visual	ADJ
alkej-102	125	20	effect	effect	NOUN
alkej-102	125	21	,	,	PUNCT
alkej-102	125	22	for	for	ADP
alkej-102	125	23	middle	middle	ADJ
alkej-102	125	24	and	and	CCONJ
alkej-102	125	25	high	high	ADJ
alkej-102	125	26	values	value	NOUN
alkej-102	125	27	of	of	ADP
alkej-102	125	28	white	white	ADJ
alkej-102	125	29	gaussian	gaussian	PROPN
alkej-102	125	30	noise	noise	NOUN
alkej-102	125	31	variances	variance	NOUN
alkej-102	125	32	,	,	PUNCT
alkej-102	125	33	which	which	PRON
alkej-102	125	34	make	make	VERB
alkej-102	125	35	the	the	DET
alkej-102	125	36	algorithm	algorithm	NOUN
alkej-102	125	37	robust	robust	ADJ
alkej-102	125	38	for	for	ADP
alkej-102	125	39	images	image	NOUN
alkej-102	125	40	attacked	attack	VERB
alkej-102	125	41	by	by	ADP
alkej-102	125	42	middle	middle	ADJ
alkej-102	125	43	and	and	CCONJ
alkej-102	125	44	large	large	ADJ
alkej-102	125	45	values	value	NOUN
alkej-102	125	46	of	of	ADP
alkej-102	125	47	noise	noise	NOUN
alkej-102	125	48	.	.	PUNCT
alkej-102	126	1	the	the	DET
alkej-102	126	2	average	average	ADJ
alkej-102	126	3	increase	increase	NOUN
alkej-102	126	4	of	of	ADP
alkej-102	126	5	psnr	psnr	NOUN
alkej-102	126	6	of	of	ADP
alkej-102	126	7	the	the	DET
alkej-102	126	8	denoised	denoise	VERB
alkej-102	126	9	image	image	NOUN
alkej-102	126	10	with	with	ADP
alkej-102	126	11	respect	respect	NOUN
alkej-102	126	12	to	to	ADP
alkej-102	126	13	noisy	noisy	ADJ
alkej-102	126	14	one	one	NUM
alkej-102	126	15	is	be	AUX
alkej-102	126	16	approximately	approximately	ADV
alkej-102	126	17	(	(	PUNCT
alkej-102	126	18	8	8	NUM
alkej-102	126	19	-	-	SYM
alkej-102	126	20	9	9	NUM
alkej-102	126	21	)	)	PUNCT
alkej-102	126	22	db	db	NOUN
alkej-102	126	23	,	,	PUNCT
alkej-102	126	24	while	while	SCONJ
alkej-102	126	25	the	the	DET
alkej-102	126	26	improvement	improvement	NOUN
alkej-102	126	27	with	with	ADP
alkej-102	126	28	respect	respect	NOUN
alkej-102	126	29	to	to	ADP
alkej-102	126	30	other	other	ADJ
alkej-102	126	31	methods	method	NOUN
alkej-102	126	32	is	be	AUX
alkej-102	126	33	up	up	ADP
alkej-102	126	34	to	to	PART
alkej-102	126	35	3.5	3.5	NUM
alkej-102	126	36	db	db	NOUN
alkej-102	127	1	.	.	PUNCT
alkej-102	127	2	notation	notation	PROPN
alkej-102	127	3	jkc	jkc	ADJ
alkej-102	127	4	discrete	discrete	ADJ
alkej-102	127	5	approximation	approximation	NOUN
alkej-102	127	6	at	at	ADP
alkej-102	127	7	the	the	DET
alkej-102	127	8	resolution	resolution	NOUN
alkej-102	127	9	j2	j2	PROPN
alkej-102	127	10	h(u	h(u	PROPN
alkej-102	127	11	,	,	PUNCT
alkej-102	127	12	v	v	NOUN
alkej-102	127	13	)	)	PUNCT
alkej-102	127	14	degraded	degraded	ADJ
alkej-102	127	15	function	function	NOUN
alkej-102	127	16	hh	hh	X
alkej-102	127	17	high	high	ADJ
alkej-102	127	18	high	high	ADJ
alkej-102	127	19	subband	subband	NOUN
alkej-102	127	20	hl	hl	PROPN
alkej-102	127	21	high	high	PROPN
alkej-102	127	22	low	low	ADJ
alkej-102	127	23	subband	subband	NOUN
alkej-102	128	1	ll	ll	AUX
alkej-102	128	2	low	low	VERB
alkej-102	128	3	low	low	ADJ
alkej-102	128	4	subband	subband	NOUN
alkej-102	129	1	lh	lh	PROPN
alkej-102	129	2	low	low	PROPN
alkej-102	129	3	high	high	ADJ
alkej-102	129	4	subband	subband	NOUN
alkej-102	129	5	psnr	psnr	PROPN
alkej-102	129	6	peak	peak	PROPN
alkej-102	129	7	signal	signal	NOUN
alkej-102	129	8	to	to	PART
alkej-102	129	9	noise	noise	VERB
alkej-102	129	10	ratio	ratio	NOUN
alkej-102	129	11	)	)	PUNCT
alkej-102	129	12	,	,	PUNCT
alkej-102	129	13	(	(	PUNCT
alkej-102	129	14	vus	vus	ADP
alkej-102	129	15	power	power	NOUN
alkej-102	129	16	spectrum	spectrum	NOUN
alkej-102	129	17	of	of	ADP
alkej-102	129	18	noise	noise	NOUN
alkej-102	129	19	)	)	PUNCT
alkej-102	129	20	,	,	PUNCT
alkej-102	129	21	(	(	PUNCT
alkej-102	129	22	vus	vus	NOUN
alkej-102	129	23	f	f	PROPN
alkej-102	129	24	power	power	PROPN
alkej-102	129	25	spectral	spectral	PROPN
alkej-102	129	26	density	density	PROPN
alkej-102	129	27	snr	snr	PROPN
alkej-102	129	28	signal	signal	VERB
alkej-102	129	29	to	to	PART
alkej-102	129	30	noise	noise	VERB
alkej-102	129	31	ratio	ratio	NOUN
alkej-102	129	32	nst	nst	ADP
alkej-102	129	33	normal	normal	ADJ
alkej-102	129	34	shrink	shrink	NOUN
alkej-102	129	35	threshold	threshold	NOUN
alkej-102	129	36	geek	geek	NOUN
alkej-102	129	37	letters	letter	NOUN
alkej-102	129	38	β	β	X
alkej-102	129	39	scale	scale	NOUN
alkej-102	129	40	parameter	parameter	NOUN
alkej-102	129	41	)	)	PUNCT
alkej-102	129	42	(	(	PUNCT
alkej-102	129	43	x	x	X
alkej-102	129	44	scaling	scale	VERB
alkej-102	129	45	function	function	NOUN
alkej-102	129	46	)	)	PUNCT
alkej-102	129	47	(	(	PUNCT
alkej-102	129	48	x	x	PROPN
alkej-102	129	49	wavelet	wavelet	PROPN
alkej-102	129	50	function	function	PROPN
alkej-102	129	51	jk	jk	PROPN
alkej-102	129	52	discrete	discrete	ADJ
alkej-102	129	53	detail	detail	NOUN
alkej-102	129	54	signal	signal	NOUN
alkej-102	129	55	at	at	ADP
alkej-102	129	56	the	the	DET
alkej-102	129	57	resolution	resolution	NOUN
alkej-102	129	58	j2	j2	PROPN
alkej-102	129	59	n	n	PROPN
alkej-102	129	60			PROPN
alkej-102	129	61			PROPN
alkej-102	129	62	standard	standard	ADJ
alkej-102	129	63	deviation	deviation	NOUN
alkej-102	129	64	of	of	ADP
alkej-102	129	65	noise	noise	NOUN
alkej-102	130	1	y	y	PROPN
alkej-102	130	2			PROPN
alkej-102	130	3			PROPN
alkej-102	130	4	standard	standard	ADJ
alkej-102	130	5	deviation	deviation	NOUN
alkej-102	130	6	of	of	ADP
alkej-102	130	7	the	the	DET
alkej-102	130	8	subband	subband	NOUN
alkej-102	130	9	2	2	PROPN
alkej-102	130	10	n	n	NOUN
alkej-102	130	11			PROPN
alkej-102	130	12			PROPN
alkej-102	130	13	noise	noise	NOUN
alkej-102	130	14	variance	variance	NOUN
alkej-102	130	15			VERB
alkej-102	130	16	threshold	threshold	NOUN
alkej-102	130	17	value	value	NOUN
alkej-102	130	18	y	y	NOUN
alkej-102	130	19	soft	soft	ADJ
alkej-102	130	20	thresholded	thresholde	VERB
alkej-102	130	21	coefficients	coefficient	NOUN
alkej-102	130	22	6	6	NUM
alkej-102	130	23	.	.	PUNCT
alkej-102	131	1	references	reference	NOUN
alkej-102	131	2	[	[	X
alkej-102	131	3	1	1	NUM
alkej-102	131	4	]	]	X
alkej-102	131	5	patil	patil	PROPN
alkej-102	131	6	,	,	PUNCT
alkej-102	131	7	a	a	PRON
alkej-102	131	8	,	,	PUNCT
alkej-102	131	9	and	and	CCONJ
alkej-102	131	10	singhai	singhai	PROPN
alkej-102	131	11	,	,	PUNCT
alkej-102	131	12	j.	j.	PROPN
alkej-102	131	13	,	,	PUNCT
alkej-102	131	14	―image	―image	AUX
alkej-102	131	15	denoising	denoise	VERB
alkej-102	131	16	using	use	VERB
alkej-102	131	17	curvelet	curvelet	NOUN
alkej-102	131	18	transform	transform	NOUN
alkej-102	131	19	:	:	PUNCT
alkej-102	131	20	an	an	DET
alkej-102	131	21	approach	approach	NOUN
alkej-102	131	22	for	for	ADP
alkej-102	131	23	edge	edge	NOUN
alkej-102	131	24	preservation‖	preservation‖	PROPN
alkej-102	131	25	,	,	PUNCT
alkej-102	131	26	journal	journal	NOUN
alkej-102	131	27	of	of	ADP
alkej-102	131	28	scientific	scientific	ADJ
alkej-102	131	29	&	&	CCONJ
alkej-102	131	30	industrial	industrial	ADJ
alkej-102	131	31	research	research	NOUN
alkej-102	131	32	,	,	PUNCT
alkej-102	131	33	vol	vol	NOUN
alkej-102	131	34	.	.	PROPN
alkej-102	131	35	69	69	NUM
alkej-102	131	36	,	,	PUNCT
alkej-102	131	37	pp	pp	ADJ
alkej-102	131	38	.	.	PUNCT
alkej-102	132	1	34	34	NUM
alkej-102	132	2	-	-	SYM
alkej-102	132	3	38	38	NUM
alkej-102	132	4	.	.	NUM
alkej-102	132	5	,	,	PUNCT
alkej-102	132	6	2010	2010	NUM
alkej-102	132	7	.	.	PUNCT
alkej-102	133	1	[	[	X
alkej-102	133	2	2	2	NUM
alkej-102	133	3	]	]	X
alkej-102	133	4	mallat	mallat	ADJ
alkej-102	133	5	,	,	PUNCT
alkej-102	133	6	s.	s.	PROPN
alkej-102	133	7	,	,	PUNCT
alkej-102	133	8	―a	―a	PROPN
alkej-102	133	9	theory	theory	NOUN
alkej-102	133	10	for	for	ADP
alkej-102	133	11	multiresolution	multiresolution	NOUN
alkej-102	133	12	signal	signal	NOUN
alkej-102	133	13	decomposition	decomposition	NOUN
alkej-102	133	14	:	:	PUNCT
alkej-102	133	15	the	the	DET
alkej-102	133	16	wavelet	wavelet	NOUN
alkej-102	133	17	representation,‖	representation,‖	PROPN
alkej-102	133	18	ieee	ieee	PROPN
alkej-102	133	19	trans	trans	PROPN
alkej-102	133	20	.	.	PUNCT
alkej-102	134	1	pattern	pattern	PROPN
alkej-102	134	2	anal	anal	PROPN
alkej-102	134	3	.	.	PUNCT
alkej-102	135	1	machine	machine	NOUN
alkej-102	135	2	intell	intell	PROPN
alkej-102	135	3	.	.	PUNCT
alkej-102	136	1	vol	vol	NOUN
alkej-102	136	2	.	.	PROPN
alkej-102	137	1	11	11	NUM
alkej-102	137	2	,	,	PUNCT
alkej-102	137	3	pp	pp	ADJ
alkej-102	137	4	.	.	PUNCT
alkej-102	138	1	674–693	674–693	NUM
alkej-102	138	2	,	,	PUNCT
alkej-102	138	3	1989	1989	NUM
alkej-102	138	4	.	.	PUNCT
alkej-102	139	1	[	[	X
alkej-102	139	2	3	3	NUM
alkej-102	139	3	]	]	PUNCT
alkej-102	139	4	donoho	donoho	NOUN
alkej-102	139	5	,	,	PUNCT
alkej-102	139	6	d.l	d.l	PROPN
alkej-102	139	7	.	.	PROPN
alkej-102	139	8	,	,	PUNCT
alkej-102	139	9	―de	―de	NOUN
alkej-102	139	10	-	-	PUNCT
alkej-102	139	11	noising	noising	NOUN
alkej-102	139	12	by	by	ADP
alkej-102	139	13	softthresholding	softthresholde	VERB
alkej-102	139	14	―	―	NUM
alkej-102	139	15	,	,	PUNCT
alkej-102	139	16	ieee	ieee	NOUN
alkej-102	139	17	transactions	transaction	NOUN
alkej-102	139	18	on	on	ADP
alkej-102	139	19	information	information	NOUN
alkej-102	139	20	theory	theory	NOUN
alkej-102	139	21	,	,	PUNCT
alkej-102	139	22	vol	vol	NOUN
alkej-102	139	23	.	.	PROPN
alkej-102	139	24	41	41	NUM
alkej-102	139	25	,	,	PUNCT
alkej-102	139	26	no.3	no.3	VERB
alkej-102	139	27	,	,	PUNCT
alkej-102	139	28	pp	pp	X
alkej-102	139	29	.	.	PUNCT
alkej-102	139	30	613627	613627	NUM
alkej-102	139	31	,	,	PUNCT
alkej-102	139	32	1995	1995	NUM
alkej-102	139	33	.	.	PUNCT
alkej-102	140	1	[	[	X
alkej-102	140	2	4	4	NUM
alkej-102	140	3	]	]	X
alkej-102	140	4	elyasi	elyasi	NOUN
alkej-102	140	5	,	,	PUNCT
alkej-102	140	6	i.	i.	NOUN
alkej-102	140	7	and	and	CCONJ
alkej-102	140	8	zermchi	zermchi	PROPN
alkej-102	140	9	,	,	PUNCT
alkej-102	140	10	s.	s.	PROPN
alkej-102	140	11	,	,	PUNCT
alkej-102	140	12	―elimination	―elimination	NOUN
alkej-102	140	13	noise	noise	NOUN
alkej-102	140	14	by	by	ADP
alkej-102	140	15	adaptive	adaptive	ADJ
alkej-102	140	16	wavelet	wavelet	NOUN
alkej-102	140	17	threshold‖	threshold‖	PROPN
alkej-102	140	18	,	,	PUNCT
alkej-102	140	19	world	world	PROPN
alkej-102	140	20	academy	academy	PROPN
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alkej-102	140	22	science	science	PROPN
alkej-102	140	23	,	,	PUNCT
alkej-102	140	24	eng	eng	PROPN
alkej-102	140	25	.	.	PROPN
alkej-102	140	26	and	and	CCONJ
alkej-102	140	27	tech	tech	NOUN
alkej-102	140	28	.	.	PUNCT
alkej-102	140	29	,	,	PUNCT
alkej-102	140	30	vol	vol	NOUN
alkej-102	140	31	.	.	PROPN
alkej-102	140	32	56	56	NUM
alkej-102	140	33	,	,	PUNCT
alkej-102	140	34	pp	pp	ADJ
alkej-102	140	35	.	.	PUNCT
alkej-102	140	36	462	462	NUM
alkej-102	140	37	-	-	SYM
alkej-102	140	38	465	465	NUM
alkej-102	140	39	,	,	PUNCT
alkej-102	140	40	2009	2009	NUM
alkej-102	140	41	.	.	PUNCT
alkej-102	141	1	[	[	X
alkej-102	141	2	5	5	NUM
alkej-102	141	3	]	]	X
alkej-102	141	4	jacob	jacob	PROPN
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alkej-102	141	6	martin	martin	PROPN
alkej-102	141	7	,	,	PUNCT
alkej-102	141	8	a.	a.	PROPN
alkej-102	141	9	,	,	PUNCT
alkej-102	141	10	―image	―image	AUX
alkej-102	141	11	denoising	denoise	VERB
alkej-102	141	12	in	in	ADP
alkej-102	141	13	the	the	DET
alkej-102	141	14	wavelet	wavelet	NOUN
alkej-102	141	15	domain	domain	NOUN
alkej-102	141	16	using	use	VERB
alkej-102	141	17	wiener	wiener	NOUN
alkej-102	141	18	filtering‖	filtering‖	PUNCT
alkej-102	141	19	ece	ece	PROPN
alkej-102	141	20	533	533	NUM
alkej-102	141	21	project	project	NOUN
alkej-102	141	22	,	,	PUNCT
alkej-102	141	23	university	university	PROPN
alkej-102	141	24	of	of	ADP
alkej-102	141	25	wisconsin	wisconsin	PROPN
alkej-102	141	26	,	,	PUNCT
alkej-102	141	27	fall	fall	VERB
alkej-102	141	28	2004	2004	NUM
alkej-102	141	29	.	.	PUNCT
alkej-102	142	1	[	[	X
alkej-102	142	2	6	6	NUM
alkej-102	142	3	]	]	X
alkej-102	142	4	jin	jin	PROPN
alkej-102	142	5	,	,	PUNCT
alkej-102	142	6	f.	f.	PROPN
alkej-102	142	7	,	,	PUNCT
alkej-102	142	8	fieguth	fieguth	PROPN
alkej-102	142	9	,	,	PUNCT
alkej-102	142	10	p.	p.	NOUN
alkej-102	142	11	,	,	PUNCT
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alkej-102	142	13	,	,	PUNCT
alkej-102	142	14	l.	l.	PROPN
alkej-102	142	15	and	and	CCONJ
alkej-102	142	16	jernigan	jernigan	PROPN
alkej-102	142	17	,	,	PUNCT
alkej-102	142	18	e.	e.	PROPN
alkej-102	142	19	,	,	PUNCT
alkej-102	142	20	―adaptive	―adaptive	ADJ
alkej-102	142	21	wiener	wiener	NOUN
alkej-102	142	22	filtering	filtering	NOUN
alkej-102	142	23	of	of	ADP
alkej-102	142	24	noisy	noisy	ADJ
alkej-102	142	25	images	image	NOUN
alkej-102	142	26	and	and	CCONJ
alkej-102	142	27	image	image	NOUN
alkej-102	142	28	sequences‖	sequences‖	PROPN
alkej-102	142	29	ieee	ieee	NOUN
alkej-102	142	30	,	,	PUNCT
alkej-102	142	31	icip	icip	NOUN
alkej-102	142	32	.	.	PUNCT
alkej-102	142	33	,	,	PUNCT
alkej-102	142	34	vol.2	vol.2	PROPN
alkej-102	142	35	,	,	PUNCT
alkej-102	142	36	pp	pp	ADJ
alkej-102	142	37	.	.	PUNCT
alkej-102	143	1	349	349	NUM
alkej-102	143	2	-	-	SYM
alkej-102	143	3	352	352	NUM
alkej-102	143	4	,	,	PUNCT
alkej-102	143	5	2003	2003	NUM
alkej-102	143	6	.	.	PUNCT
alkej-102	144	1	[	[	X
alkej-102	144	2	7	7	NUM
alkej-102	144	3	]	]	PUNCT
alkej-102	144	4	pesquet	pesquet	NOUN
alkej-102	144	5	,	,	PUNCT
alkej-102	144	6	j.c	j.c	PROPN
alkej-102	144	7	.	.	PROPN
alkej-102	144	8	,	,	PUNCT
alkej-102	144	9	krim	krim	PROPN
alkej-102	144	10	,	,	PUNCT
alkej-102	144	11	h.	h.	PROPN
alkej-102	144	12	and	and	CCONJ
alkej-102	144	13	carfantan	carfantan	PROPN
alkej-102	144	14	,	,	PUNCT
alkej-102	144	15	h.	h.	PROPN
alkej-102	144	16	,	,	PUNCT
alkej-102	144	17	―time	―time	ADJ
alkej-102	144	18	-	-	ADJ
alkej-102	144	19	invariant	invariant	ADJ
alkej-102	144	20	orthonormal	orthonormal	ADJ
alkej-102	144	21	wavelet	wavelet	NOUN
alkej-102	144	22	representations,‖	representations,‖	PROPN
alkej-102	144	23	ieee	ieee	PROPN
alkej-102	144	24	trans	trans	PROPN
alkej-102	144	25	.	.	PROPN
alkej-102	144	26	signal	signal	PROPN
alkej-102	144	27	processing	processing	NOUN
alkej-102	144	28	,	,	PUNCT
alkej-102	144	29	vol	vol	NOUN
alkej-102	144	30	.	.	PROPN
alkej-102	144	31	44	44	NUM
alkej-102	144	32	,	,	PUNCT
alkej-102	144	33	pp.1964–1970	pp.1964–1970	PROPN
alkej-102	144	34	,	,	PUNCT
alkej-102	144	35	1996	1996	NUM
alkej-102	144	36	.	.	PUNCT
alkej-102	145	1	[	[	X
alkej-102	145	2	8	8	NUM
alkej-102	145	3	]	]	X
alkej-102	145	4	wang	wang	PROPN
alkej-102	145	5	,	,	PUNCT
alkej-102	145	6	x.h	x.h	PROPN
alkej-102	145	7	.	.	PROPN
alkej-102	145	8	,	,	PUNCT
alkej-102	145	9	istepanian	istepanian	PROPN
alkej-102	145	10	,	,	PUNCT
alkej-102	145	11	s.h	s.h	PROPN
alkej-102	145	12	.	.	PROPN
alkej-102	145	13	,	,	PUNCT
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alkej-102	145	17	y.h	y.h	PROPN
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alkej-102	145	20	―microarray	―microarray	ADP
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alkej-102	145	22	enhancement	enhancement	NOUN
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alkej-102	145	24	denoising	denoise	VERB
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alkej-102	145	28	transform‖	transform‖	PROPN
alkej-102	145	29	,	,	PUNCT
alkej-102	145	30	ieee	ieee	NOUN
alkej-102	145	31	trans	tran	NOUN
alkej-102	145	32	.	.	PUNCT
alkej-102	146	1	on	on	ADP
alkej-102	146	2	nanobioscience	nanobioscience	NOUN
alkej-102	146	3	,	,	PUNCT
alkej-102	146	4	vol.2	vol.2	PROPN
alkej-102	146	5	,	,	PUNCT
alkej-102	146	6	no	no	INTJ
alkej-102	146	7	.	.	NOUN
alkej-102	146	8	4	4	NUM
alkej-102	146	9	,	,	PUNCT
alkej-102	146	10	pp	pp	ADJ
alkej-102	146	11	.	.	PUNCT
alkej-102	147	1	184	184	NUM
alkej-102	147	2	-	-	SYM
alkej-102	147	3	189	189	NUM
alkej-102	147	4	,	,	PUNCT
alkej-102	147	5	2003	2003	NUM
alkej-102	147	6	.	.	PUNCT
alkej-102	148	1	[	[	X
alkej-102	148	2	9	9	NUM
alkej-102	148	3	]	]	X
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alkej-102	148	10	,	,	PUNCT
alkej-102	148	11	r.e	r.e	PROPN
alkej-102	148	12	.	.	PROPN
alkej-102	148	13	,	,	PUNCT
alkej-102	148	14	and	and	CCONJ
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alkej-102	148	16	,	,	PUNCT
alkej-102	148	17	s.l	s.l	PROPN
alkej-102	148	18	.	.	PROPN
alkej-102	148	19	,	,	PUNCT
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alkej-102	148	22	using	use	VERB
alkej-102	148	23	matlab	matlab	PROPN
alkej-102	148	24	processing‖	processing‖	PROPN
alkej-102	148	25	,	,	PUNCT
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alkej-102	148	27	hall	hall	NOUN
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alkej-102	148	31	,	,	PUNCT
alkej-102	148	32	2007	2007	NUM
alkej-102	148	33	.	.	PUNCT
alkej-102	149	1	[	[	X
alkej-102	149	2	10	10	NUM
alkej-102	149	3	]	]	X
alkej-102	149	4	johnstone	johnstone	PROPN
alkej-102	149	5	,	,	PUNCT
alkej-102	149	6	i.m	i.m	PROPN
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alkej-102	149	11	b.w	b.w	PROPN
alkej-102	149	12	.	.	PROPN
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alkej-102	149	16	estimators	estimator	NOUN
alkej-102	149	17	for	for	ADP
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alkej-102	149	26	soc	soc	NOUN
alkej-102	149	27	.	.	PUNCT
alkej-102	149	28	,	,	PUNCT
alkej-102	149	29	vol	vol	NOUN
alkej-102	149	30	.	.	PUNCT
alkej-102	149	31	b59	b59	NOUN
alkej-102	149	32	,	,	PUNCT
alkej-102	149	33	pp	pp	ADP
alkej-102	149	34	.	.	PUNCT
alkej-102	150	1	319	319	NUM
alkej-102	150	2	-	-	SYM
alkej-102	150	3	351	351	NUM
alkej-102	150	4	,	,	PUNCT
alkej-102	150	5	1997	1997	NUM
alkej-102	150	6	.	.	PUNCT
alkej-102	151	1	[	[	X
alkej-102	151	2	11	11	NUM
alkej-102	151	3	]	]	X
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alkej-102	151	6	a.a	a.a	PROPN
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alkej-102	151	22	color	color	NOUN
alkej-102	151	23	image	image	NOUN
alkej-102	151	24	coding	code	VERB
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alkej-102	151	27	blocktree	blocktree	NOUN
alkej-102	151	28	approach‖	approach‖	PROPN
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alkej-102	151	30	ieee	ieee	NOUN
alkej-102	151	31	,	,	PUNCT
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alkej-102	151	33	,	,	PUNCT
alkej-102	151	34	pp	pp	ADV
alkej-102	151	35	.	.	PUNCT
alkej-102	152	1	1889	1889	NUM
alkej-102	152	2	-	-	SYM
alkej-102	152	3	1892	1892	NUM
alkej-102	152	4	,	,	PUNCT
alkej-102	152	5	2006	2006	NUM
alkej-102	152	6	.	.	PUNCT
alkej-102	153	1	(	(	PUNCT
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alkej-102	153	3	)	)	PUNCT
alkej-102	153	4	26	26	NUM
alkej-102	153	5	-	-	SYM
alkej-102	153	6	18	18	NUM
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alkej-102	153	9	،	،	PROPN
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alkej-102	153	11	الخىارزمي	الخىارزمي	PROPN
alkej-102	153	12	الهىذسية	الهىذسية	PROPN
alkej-102	153	13	المجلذإيمان	المجلذإيمان	PROPN
alkej-102	153	14	محمذ	محمذ	PROPN
alkej-102	153	15	جعفر	جعفر	VERB
alkej-102	153	16	26	26	NUM
alkej-102	153	17	إزالة	إزالة	NOUN
alkej-102	153	18	الضىضاء	الضىضاء	NOUN
alkej-102	153	19	مه	مه	ADP
alkej-102	153	20	الصىر	الصىر	PROPN
alkej-102	153	21	الملىوة	الملىوة	PROPN
alkej-102	153	22	باستعمال	باستعمال	PROPN
alkej-102	153	23	تحىيلة	تحىيلة	PROPN
alkej-102	153	24	المىيجة	المىيجة	PROPN
alkej-102	153	25	المستقرة	المستقرة	PROPN
alkej-102	153	26	ومرشح	ومرشح	PROPN
alkej-102	153	27	ويىر	ويىر	PROPN
alkej-102	153	28	المتكيّف	المتكيّف	PROPN
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alkej-102	153	30	محمذ	محمذ	PROPN
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alkej-102	153	32	علىان	علىان	PROPN
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alkej-102	153	34	تغداد	تغداد	PROPN
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alkej-102	153	39	/	/	SYM
alkej-102	153	40	قسى	قسى	PROPN
alkej-102	153	41	عهىو	عهىو	PROPN
alkej-102	153	42	انحاسثاخ	انحاسثاخ	PROPN
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alkej-102	153	46	االنكتزوَي	االنكتزوَي	PROPN
alkej-102	153	47	الخالصة	الخالصة	PROPN
alkej-102	153	48	انعديد	انعديد	AUX
alkej-102	153	49	يٍ	يٍ	PROPN
alkej-102	153	50	اندراساخ	اندراساخ	VERB
alkej-102	153	51	.	.	PUNCT
alkej-102	154	1	هي	هي	AUX
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alkej-102	154	5	عًهياخ	عًهياخ	ADJ
alkej-102	154	6	انًعانجح	انًعانجح	PROPN
alkej-102	154	7	انصىريحgaussianإٌ	انصىريحgaussianإٌ	PART
alkej-102	154	8	عًهيح	عًهيح	PROPN
alkej-102	154	9	إسانح	إسانح	PROPN
alkej-102	154	10	انضىضاء	انضىضاء	VERB
alkej-102	154	11	يٍ	يٍ	PROPN
alkej-102	154	12	انصىر	انصىر	NOUN
alkej-102	154	13	انًتأثزج	انًتأثزج	PROPN
alkej-102	154	14	تضىضاء	تضىضاء	VERB
alkej-102	154	15	يٍ	يٍ	PROPN
alkej-102	154	16	َىع	َىع	PROPN
alkej-102	154	17	اعتًدخ	اعتًدخ	PUNCT
alkej-102	154	18	عهى	عهى	NOUN
alkej-102	154	19	تطثيق	تطثيق	PROPN
alkej-102	154	20	تقُيح	تقُيح	PROPN
alkej-102	154	21	انعتثح	انعتثح	PROPN
alkej-102	154	22	عهى	عهى	PROPN
alkej-102	155	1	يعايالخ	يعايالخ	PROPN
alkej-102	155	2	انًىيجح	انًىيجح	PROPN
alkej-102	155	3	،	،	PROPN
alkej-102	155	4	إٌ	إٌ	NOUN
alkej-102	155	5	يعظى	يعظى	PROPN
alkej-102	155	6	هذِ	هذِ	X
alkej-102	155	7	اندراساخ	اندراساخ	PROPN
alkej-102	155	8	ركشخ	ركشخ	PROPN
alkej-102	155	9	عهى	عهى	PROPN
alkej-102	155	10	انتشكيم	انتشكيم	PROPN
alkej-102	155	11	اإلحصائي	اإلحصائي	PROPN
alkej-102	155	12	نًعايالخ	نًعايالخ	NUM
alkej-102	155	13	انًىيجح	انًىيجح	PROPN
alkej-102	155	14	وعهى	وعهى	PROPN
alkej-102	155	15	االختيار	االختيار	PROPN
alkej-102	155	16	األيثم	األيثم	PROPN
alkej-102	155	17	،	،	PROPN
alkej-102	155	18	حيث	حيث	PROPN
alkej-102	155	19	wienerيقدو	wienerيقدو	PROPN
alkej-102	155	20	هذا	هذا	NOUN
alkej-102	155	21	انثحث	انثحث	PROPN
alkej-102	155	22	طزيقح	طزيقح	PROPN
alkej-102	155	23	جديدج	جديدج	PROPN
alkej-102	155	24	إلسانح	إلسانح	PROPN
alkej-102	155	25	انضىضاء	انضىضاء	PROPN
alkej-102	155	26	تىاسطح	تىاسطح	PROPN
alkej-102	155	27	ديج	ديج	PROPN
alkej-102	155	28	تقُيح	تقُيح	PROPN
alkej-102	155	29	إسانح	إسانح	PROPN
alkej-102	155	30	انضىضاء	انضىضاء	VERB
alkej-102	155	31	تاستعًال	تاستعًال	PUNCT
alkej-102	155	32	تحىيهح	تحىيهح	PROPN
alkej-102	156	1	انًىيجح	انًىيجح	PROPN
alkej-102	156	2	انًستقزج	انًستقزج	PROPN
alkej-102	156	3	ويزشح	ويزشح	PROPN
alkej-102	156	4	.	.	PUNCT
alkej-102	157	1	نقيًح	نقيًح	PROPN
alkej-102	157	2	انعتثح	انعتثح	PROPN
alkej-102	157	3	عهى	عهى	PROPN
alkej-102	157	4	انصىرج	انصىرج	NOUN
alkej-102	157	5	انًستزجعح	انًستزجعح	PROPN
alkej-102	157	6	يٍ	يٍ	PROPN
alkej-102	157	7	يعايالخ	يعايالخ	PROPN
alkej-102	157	8	انتقزية	انتقزية	PROPN
alkej-102	157	9	فقظ	فقظ	PROPN
alkej-102	157	10	تيًُا	تيًُا	PUNCT
alkej-102	157	11	يتى	يتى	PROPN
alkej-102	157	12	تطثيق	تطثيق	PROPN
alkej-102	157	13	تقُيح	تقُيح	PROPN
alkej-102	157	14	انعتثح	انعتثح	PROPN
alkej-102	157	15	عهى	عهى	PROPN
alkej-102	158	1	قيى	قيى	PROPN
alkej-102	159	1	يعايالخ	يعايالخ	PROPN
alkej-102	159	2	انتفاصيم	انتفاصيم	PROPN
alkej-102	159	3	انتي	انتي	PROPN
alkej-102	159	4	تى	تى	ADP
alkej-102	159	5	انحصىل	انحصىل	PROPN
alkej-102	159	6	wienerيتى	wienerيتى	PROPN
alkej-102	159	7	تطثيق	تطثيق	PROPN
alkej-102	159	8	يزشح	يزشح	PROPN
alkej-102	159	9	عهى	عهى	PROPN
alkej-102	159	10	صىر	صىر	PROPN
alkej-102	159	11	يهىَح	يهىَح	NUM
alkej-102	159	12	ويهىثح	ويهىثح	PROPN
alkej-102	159	13	r2010aنقد	r2010aنقد	NOUN
alkej-102	159	14	تى	تى	INTJ
alkej-102	159	15	تُفيذ	تُفيذ	PUNCT
alkej-102	159	16	انطزيقح	انطزيقح	ADJ
alkej-102	159	17	انًقتزحح	انًقتزحح	PROPN
alkej-102	159	18	تاستعًال	تاستعًال	PROPN
alkej-102	159	19	تزَايج	تزَايج	PROPN
alkej-102	159	20	ياتالب	ياتالب	PROPN
alkej-102	159	21	.	.	PUNCT
alkej-102	160	1	عهيها	عهيها	PROPN
alkej-102	160	2	تتطثيق	تتطثيق	VERB
alkej-102	160	3	تحىيهح	تحىيهح	PROPN
alkej-102	160	4	انًىيجح	انًىيجح	PROPN
alkej-102	161	1	انًستقزج	انًستقزج	PROPN
alkej-102	161	2	ويٍ	ويٍ	PROPN
alkej-102	161	3	ثى	ثى	PRON
alkej-102	161	4	ديج	ديج	AUX
alkej-102	161	5	انُتيجتيٍ	انُتيجتيٍ	PROPN
alkej-102	161	6	.	.	PUNCT
alkej-102	162	1	3.5dbأظهزخ	3.5dbأظهزخ	NOUN
alkej-102	163	1	انُتائج	انُتائج	PROPN
alkej-102	163	2	تحسيٍ	تحسيٍ	PROPN
alkej-102	163	3	واضح	واضح	PROPN
alkej-102	163	4	نهصىر	نهصىر	PROPN
alkej-102	163	5	وصم	وصم	PROPN
alkej-102	163	6	نحد	نحد	NOUN
alkej-102	163	7	.	.	PUNCT
alkej-102	164	1	gaussianتضىضاء	gaussianتضىضاء	VERB
alkej-102	164	2	يٍ	يٍ	PROPN
alkej-102	164	3	َىع	َىع	NOUN