id	sid	tid	token	lemma	pos
cet-3935	1	1	chemical	chemical	NOUN
cet-3935	1	2	engineering	engineering	NOUN
cet-3935	1	3	transactions	transaction	NOUN
cet-3935	1	4	vol	vol	NOUN
cet-3935	1	5	.	.	PROPN
cet-3935	2	1	51	51	NUM
cet-3935	2	2	,	,	PUNCT
cet-3935	2	3	2016	2016	NUM
cet-3935	2	4	a	a	DET
cet-3935	2	5	publication	publication	NOUN
cet-3935	2	6	of	of	ADP
cet-3935	2	7	the	the	DET
cet-3935	2	8	italian	italian	ADJ
cet-3935	2	9	association	association	NOUN
cet-3935	2	10	of	of	ADP
cet-3935	2	11	chemical	chemical	PROPN
cet-3935	2	12	engineering	engineering	NOUN
cet-3935	2	13	online	online	ADV
cet-3935	2	14	at	at	ADP
cet-3935	2	15	www.aidic.it/cet	www.aidic.it/cet	PROPN
cet-3935	2	16	guest	guest	NOUN
cet-3935	2	17	editors	editor	NOUN
cet-3935	2	18	:	:	PUNCT
cet-3935	2	19	tichun	tichun	PROPN
cet-3935	2	20	wang	wang	PROPN
cet-3935	2	21	,	,	PUNCT
cet-3935	2	22	hongyang	hongyang	PROPN
cet-3935	2	23	zhang	zhang	PROPN
cet-3935	2	24	,	,	PUNCT
cet-3935	2	25	lei	lei	PROPN
cet-3935	2	26	tian	tian	ADJ
cet-3935	2	27	copyright	copyright	NOUN
cet-3935	2	28	©	©	PROPN
cet-3935	2	29	2016	2016	NUM
cet-3935	2	30	,	,	PUNCT
cet-3935	2	31	aidic	aidic	ADJ
cet-3935	2	32	servizi	servizi	PROPN
cet-3935	2	33	s.r.l	s.r.l	NOUN
cet-3935	2	34	.	.	PUNCT
cet-3935	2	35	,	,	PUNCT
cet-3935	2	36	isbn	isbn	PROPN
cet-3935	2	37	978	978	NUM
cet-3935	2	38	-	-	SYM
cet-3935	2	39	88	88	NUM
cet-3935	2	40	-	-	PUNCT
cet-3935	2	41	95608	95608	NUM
cet-3935	2	42	-	-	PUNCT
cet-3935	2	43	43	43	NUM
cet-3935	2	44	-	-	SYM
cet-3935	2	45	3	3	NUM
cet-3935	2	46	;	;	PUNCT
cet-3935	2	47	issn	issn	PROPN
cet-3935	2	48	2283	2283	NUM
cet-3935	2	49	-	-	SYM
cet-3935	2	50	9216	9216	NUM
cet-3935	2	51	a	a	DET
cet-3935	2	52	new	new	ADJ
cet-3935	2	53	video	video	NOUN
cet-3935	2	54	super	super	ADJ
cet-3935	2	55	-	-	ADJ
cet-3935	2	56	resolution	resolution	ADJ
cet-3935	2	57	reconstruction	reconstruction	NOUN
cet-3935	2	58	algorithm	algorithm	NOUN
cet-3935	2	59	based	base	VERB
cet-3935	2	60	on	on	ADP
cet-3935	2	61	compressive	compressive	ADJ
cet-3935	2	62	sensing	sense	VERB
cet-3935	2	63	ling	ling	PROPN
cet-3935	2	64	tang	tang	PROPN
cet-3935	2	65	*	*	PROPN
cet-3935	2	66	,	,	PUNCT
cet-3935	2	67	hong	hong	NOUN
cet-3935	2	68	song	song	NOUN
cet-3935	2	69	,	,	PUNCT
cet-3935	2	70	mingju	mingju	NOUN
cet-3935	2	71	chen	chen	PROPN
cet-3935	2	72	,	,	PUNCT
cet-3935	2	73	yumei	yumei	PROPN
cet-3935	2	74	chen	chen	PROPN
cet-3935	2	75	college	college	PROPN
cet-3935	2	76	of	of	ADP
cet-3935	2	77	automation	automation	NOUN
cet-3935	2	78	and	and	CCONJ
cet-3935	2	79	electronic	electronic	ADJ
cet-3935	2	80	information	information	NOUN
cet-3935	2	81	,	,	PUNCT
cet-3935	2	82	sichuan	sichuan	PROPN
cet-3935	2	83	university	university	PROPN
cet-3935	2	84	of	of	ADP
cet-3935	2	85	science	science	PROPN
cet-3935	2	86	&	&	CCONJ
cet-3935	2	87	engineering	engineering	PROPN
cet-3935	2	88	,	,	PUNCT
cet-3935	2	89	zigong	zigong	PROPN
cet-3935	2	90	,	,	PUNCT
cet-3935	2	91	643000	643000	NUM
cet-3935	2	92	,	,	PUNCT
cet-3935	2	93	sichuan	sichuan	PROPN
cet-3935	2	94	fashion-kitty@163.com	fashion-kitty@163.com	PROPN
cet-3935	2	95	compressive	compressive	PROPN
cet-3935	2	96	sensing(cs	sensing(cs	PROPN
cet-3935	2	97	)	)	PUNCT
cet-3935	2	98	theory	theory	NOUN
cet-3935	2	99	can	can	AUX
cet-3935	2	100	reconstruct	reconstruct	VERB
cet-3935	2	101	the	the	DET
cet-3935	2	102	original	original	ADJ
cet-3935	2	103	images	image	NOUN
cet-3935	2	104	from	from	ADP
cet-3935	2	105	the	the	DET
cet-3935	2	106	less	less	ADJ
cet-3935	2	107	measurements	measurement	NOUN
cet-3935	2	108	with	with	ADP
cet-3935	2	109	using	use	VERB
cet-3935	2	110	the	the	DET
cet-3935	2	111	priors	prior	NOUN
cet-3935	2	112	of	of	ADP
cet-3935	2	113	the	the	DET
cet-3935	2	114	image	image	NOUN
cet-3935	2	115	sparse	sparse	ADJ
cet-3935	2	116	representation	representation	NOUN
cet-3935	2	117	.	.	PUNCT
cet-3935	3	1	the	the	DET
cet-3935	3	2	cs	cs	PROPN
cet-3935	3	3	theory	theory	NOUN
cet-3935	3	4	is	be	AUX
cet-3935	3	5	applied	apply	VERB
cet-3935	3	6	into	into	ADP
cet-3935	3	7	the	the	DET
cet-3935	3	8	video	video	NOUN
cet-3935	3	9	super	super	ADJ
cet-3935	3	10	-	-	ADJ
cet-3935	3	11	resolution(sr	resolution(sr	ADJ
cet-3935	3	12	)	)	PUNCT
cet-3935	3	13	reconstruction	reconstruction	NOUN
cet-3935	3	14	,	,	PUNCT
cet-3935	3	15	and	and	CCONJ
cet-3935	3	16	a	a	DET
cet-3935	3	17	new	new	ADJ
cet-3935	3	18	algorithm	algorithm	NOUN
cet-3935	3	19	based	base	VERB
cet-3935	3	20	on	on	ADP
cet-3935	3	21	wavelet	wavelet	NOUN
cet-3935	3	22	transform	transform	NOUN
cet-3935	3	23	is	be	AUX
cet-3935	3	24	proposed	propose	VERB
cet-3935	3	25	in	in	ADP
cet-3935	3	26	this	this	DET
cet-3935	3	27	paper	paper	NOUN
cet-3935	3	28	.	.	PUNCT
cet-3935	4	1	firstly	firstly	ADV
cet-3935	4	2	,	,	PUNCT
cet-3935	4	3	wavelet	wavelet	NOUN
cet-3935	4	4	transform	transform	NOUN
cet-3935	4	5	is	be	AUX
cet-3935	4	6	used	use	VERB
cet-3935	4	7	to	to	PART
cet-3935	4	8	decompose	decompose	VERB
cet-3935	4	9	the	the	DET
cet-3935	4	10	low	low	ADJ
cet-3935	4	11	resolution	resolution	NOUN
cet-3935	4	12	image	image	NOUN
cet-3935	4	13	so	so	SCONJ
cet-3935	4	14	as	as	SCONJ
cet-3935	4	15	to	to	PART
cet-3935	4	16	get	get	VERB
cet-3935	4	17	the	the	DET
cet-3935	4	18	low	low	ADJ
cet-3935	4	19	frequency	frequency	NOUN
cet-3935	4	20	and	and	CCONJ
cet-3935	4	21	high	high	ADJ
cet-3935	4	22	frequency	frequency	NOUN
cet-3935	4	23	sub	sub	NOUN
cet-3935	4	24	bands	band	NOUN
cet-3935	4	25	,	,	PUNCT
cet-3935	4	26	then	then	ADV
cet-3935	4	27	the	the	DET
cet-3935	4	28	sub	sub	NOUN
cet-3935	4	29	bands	band	NOUN
cet-3935	4	30	are	be	AUX
cet-3935	4	31	reconstructed	reconstruct	VERB
cet-3935	4	32	respectively	respectively	ADV
cet-3935	4	33	by	by	ADP
cet-3935	4	34	using	use	VERB
cet-3935	4	35	cs	cs	PROPN
cet-3935	4	36	method	method	NOUN
cet-3935	4	37	based	base	VERB
cet-3935	4	38	on	on	ADP
cet-3935	4	39	the	the	DET
cet-3935	4	40	orthogonal	orthogonal	ADJ
cet-3935	4	41	matching	matching	NOUN
cet-3935	4	42	pursuit(omp	pursuit(omp	NOUN
cet-3935	4	43	)	)	PUNCT
cet-3935	4	44	.	.	PUNCT
cet-3935	5	1	finally	finally	ADV
cet-3935	5	2	,	,	PUNCT
cet-3935	5	3	the	the	DET
cet-3935	5	4	reconstruction	reconstruction	NOUN
cet-3935	5	5	image	image	NOUN
cet-3935	5	6	can	can	AUX
cet-3935	5	7	be	be	AUX
cet-3935	5	8	get	get	VERB
cet-3935	5	9	by	by	ADP
cet-3935	5	10	the	the	DET
cet-3935	5	11	wavelet	wavelet	NOUN
cet-3935	5	12	inverse	inverse	NOUN
cet-3935	5	13	transform	transform	NOUN
cet-3935	5	14	.	.	PUNCT
cet-3935	6	1	the	the	DET
cet-3935	6	2	experimental	experimental	ADJ
cet-3935	6	3	results	result	NOUN
cet-3935	6	4	show	show	VERB
cet-3935	6	5	that	that	SCONJ
cet-3935	6	6	proposed	propose	VERB
cet-3935	6	7	algorithm	algorithm	NOUN
cet-3935	6	8	can	can	AUX
cet-3935	6	9	obtain	obtain	VERB
cet-3935	6	10	better	well	ADJ
cet-3935	6	11	reconstruction	reconstruction	NOUN
cet-3935	6	12	image	image	NOUN
cet-3935	6	13	visual	visual	ADJ
cet-3935	6	14	effect	effect	NOUN
cet-3935	6	15	and	and	CCONJ
cet-3935	6	16	has	have	VERB
cet-3935	6	17	higher	high	ADJ
cet-3935	6	18	precision	precision	NOUN
cet-3935	6	19	.	.	PUNCT
cet-3935	7	1	under	under	ADP
cet-3935	7	2	different	different	ADJ
cet-3935	7	3	iterations	iteration	NOUN
cet-3935	7	4	and	and	CCONJ
cet-3935	7	5	magnification	magnification	NOUN
cet-3935	7	6	level	level	NOUN
cet-3935	7	7	the	the	DET
cet-3935	7	8	quality	quality	NOUN
cet-3935	7	9	of	of	ADP
cet-3935	7	10	the	the	DET
cet-3935	7	11	reconstruction	reconstruction	NOUN
cet-3935	7	12	image	image	NOUN
cet-3935	7	13	is	be	AUX
cet-3935	7	14	also	also	ADV
cet-3935	7	15	better	well	ADJ
cet-3935	7	16	.	.	PUNCT
cet-3935	8	1	1	1	X
cet-3935	8	2	.	.	X
cet-3935	8	3	introduction	introduction	NOUN
cet-3935	8	4	compressive	compressive	ADJ
cet-3935	8	5	sensing	sense	VERB
cet-3935	8	6	(	(	PUNCT
cet-3935	8	7	cs	cs	ADJ
cet-3935	8	8	)	)	PUNCT
cet-3935	8	9	theory	theory	NOUN
cet-3935	8	10	proposed	propose	VERB
cet-3935	8	11	by	by	ADP
cet-3935	8	12	candes	cande	NOUN
cet-3935	8	13	and	and	CCONJ
cet-3935	8	14	donoho	donoho	NOUN
cet-3935	8	15	et	et	PROPN
cet-3935	8	16	al	al	PROPN
cet-3935	8	17	.	.	PROPN
cet-3935	9	1	(	(	PUNCT
cet-3935	9	2	2006	2006	NUM
cet-3935	9	3	)	)	PUNCT
cet-3935	9	4	breaks	break	VERB
cet-3935	9	5	through	through	ADP
cet-3935	9	6	the	the	DET
cet-3935	9	7	traditional	traditional	ADJ
cet-3935	9	8	sampling	sampling	NOUN
cet-3935	9	9	theory	theory	NOUN
cet-3935	9	10	of	of	ADP
cet-3935	9	11	shannon	shannon	PROPN
cet-3935	9	12	.	.	PUNCT
cet-3935	10	1	the	the	DET
cet-3935	10	2	signals	signal	NOUN
cet-3935	10	3	can	can	AUX
cet-3935	10	4	be	be	AUX
cet-3935	10	5	sampled	sample	VERB
cet-3935	10	6	with	with	ADP
cet-3935	10	7	the	the	DET
cet-3935	10	8	rate	rate	NOUN
cet-3935	10	9	far	far	ADV
cet-3935	10	10	below	below	ADP
cet-3935	10	11	the	the	DET
cet-3935	10	12	nyquist	nyquist	NOUN
cet-3935	10	13	sampling	sample	VERB
cet-3935	10	14	theory	theory	NOUN
cet-3935	10	15	and	and	CCONJ
cet-3935	10	16	compressed	compress	VERB
cet-3935	10	17	at	at	ADP
cet-3935	10	18	the	the	DET
cet-3935	10	19	same	same	ADJ
cet-3935	10	20	time	time	NOUN
cet-3935	10	21	.	.	PUNCT
cet-3935	11	1	based	base	VERB
cet-3935	11	2	on	on	ADP
cet-3935	11	3	the	the	DET
cet-3935	11	4	assumption	assumption	NOUN
cet-3935	11	5	of	of	ADP
cet-3935	11	6	the	the	DET
cet-3935	11	7	image	image	NOUN
cet-3935	11	8	sparse	sparse	ADJ
cet-3935	11	9	representation	representation	NOUN
cet-3935	11	10	,	,	PUNCT
cet-3935	11	11	the	the	DET
cet-3935	11	12	original	original	ADJ
cet-3935	11	13	signal	signal	NOUN
cet-3935	11	14	can	can	AUX
cet-3935	11	15	be	be	AUX
cet-3935	11	16	reconstructed	reconstruct	VERB
cet-3935	11	17	accurately	accurately	ADV
cet-3935	11	18	at	at	ADP
cet-3935	11	19	the	the	DET
cet-3935	11	20	receiver	receiver	NOUN
cet-3935	11	21	by	by	ADP
cet-3935	11	22	solving	solve	VERB
cet-3935	11	23	the	the	DET
cet-3935	11	24	optimization	optimization	NOUN
cet-3935	11	25	problem	problem	NOUN
cet-3935	11	26	.	.	PUNCT
cet-3935	12	1	compressed	compress	VERB
cet-3935	12	2	sensing	sense	VERB
cet-3935	12	3	theory	theory	NOUN
cet-3935	12	4	is	be	AUX
cet-3935	12	5	widely	widely	ADV
cet-3935	12	6	used	use	VERB
cet-3935	12	7	after	after	ADP
cet-3935	12	8	being	be	AUX
cet-3935	12	9	proposed	propose	VERB
cet-3935	12	10	,	,	PUNCT
cet-3935	12	11	and	and	CCONJ
cet-3935	12	12	many	many	ADJ
cet-3935	12	13	practical	practical	ADJ
cet-3935	12	14	applications	application	NOUN
cet-3935	12	15	are	be	AUX
cet-3935	12	16	related	relate	VERB
cet-3935	12	17	to	to	ADP
cet-3935	12	18	the	the	DET
cet-3935	12	19	acquisition	acquisition	NOUN
cet-3935	12	20	of	of	ADP
cet-3935	12	21	video	video	NOUN
cet-3935	12	22	images	image	NOUN
cet-3935	12	23	(	(	PUNCT
cet-3935	12	24	li	li	PROPN
cet-3935	12	25	et	et	PROPN
cet-3935	12	26	al	al	PROPN
cet-3935	12	27	.	.	PROPN
cet-3935	12	28	,	,	PUNCT
cet-3935	12	29	2012	2012	NUM
cet-3935	12	30	)	)	PUNCT
cet-3935	12	31	,	,	PUNCT
cet-3935	12	32	therefore	therefore	ADV
cet-3935	12	33	,	,	PUNCT
cet-3935	12	34	it	it	PRON
cet-3935	12	35	has	have	VERB
cet-3935	12	36	great	great	ADJ
cet-3935	12	37	practical	practical	ADJ
cet-3935	12	38	value	value	NOUN
cet-3935	12	39	to	to	PART
cet-3935	12	40	study	study	VERB
cet-3935	12	41	the	the	DET
cet-3935	12	42	effective	effective	ADJ
cet-3935	12	43	video	video	NOUN
cet-3935	12	44	image	image	NOUN
cet-3935	12	45	reconstruction	reconstruction	NOUN
cet-3935	12	46	based	base	VERB
cet-3935	12	47	on	on	ADP
cet-3935	12	48	cs	cs	PROPN
cet-3935	12	49	.	.	PROPN
cet-3935	12	50	at	at	ADP
cet-3935	12	51	present	present	ADJ
cet-3935	12	52	,	,	PUNCT
cet-3935	12	53	cs	cs	PROPN
cet-3935	12	54	video	video	NOUN
cet-3935	12	55	image	image	NOUN
cet-3935	12	56	reconstruction	reconstruction	NOUN
cet-3935	12	57	algorithms	algorithm	NOUN
cet-3935	12	58	are	be	AUX
cet-3935	12	59	divided	divide	VERB
cet-3935	12	60	into	into	ADP
cet-3935	12	61	two	two	NUM
cet-3935	12	62	parts	part	NOUN
cet-3935	12	63	,	,	PUNCT
cet-3935	12	64	which	which	PRON
cet-3935	12	65	are	be	AUX
cet-3935	12	66	video	video	NOUN
cet-3935	12	67	signal	signal	NOUN
cet-3935	12	68	cs	cs	PROPN
cet-3935	12	69	measurement	measurement	NOUN
cet-3935	12	70	and	and	CCONJ
cet-3935	12	71	video	video	NOUN
cet-3935	12	72	signal	signal	NOUN
cet-3935	12	73	reconstruction	reconstruction	NOUN
cet-3935	12	74	.	.	PUNCT
cet-3935	13	1	the	the	DET
cet-3935	13	2	operation	operation	NOUN
cet-3935	13	3	of	of	ADP
cet-3935	13	4	the	the	DET
cet-3935	13	5	measurement	measurement	NOUN
cet-3935	13	6	is	be	AUX
cet-3935	13	7	low	low	ADJ
cet-3935	13	8	,	,	PUNCT
cet-3935	13	9	thus	thus	ADV
cet-3935	13	10	in	in	ADP
cet-3935	13	11	the	the	DET
cet-3935	13	12	process	process	NOUN
cet-3935	13	13	of	of	ADP
cet-3935	13	14	reconstruction	reconstruction	NOUN
cet-3935	13	15	,	,	PUNCT
cet-3935	13	16	the	the	DET
cet-3935	13	17	iterative	iterative	NOUN
cet-3935	13	18	solution	solution	NOUN
cet-3935	13	19	is	be	AUX
cet-3935	13	20	needed	need	VERB
cet-3935	13	21	to	to	PART
cet-3935	13	22	solve	solve	VERB
cet-3935	13	23	the	the	DET
cet-3935	13	24	optimization	optimization	NOUN
cet-3935	13	25	problem	problem	NOUN
cet-3935	13	26	with	with	ADP
cet-3935	13	27	high	high	ADJ
cet-3935	13	28	complexity	complexity	NOUN
cet-3935	13	29	.	.	PUNCT
cet-3935	14	1	in	in	ADP
cet-3935	14	2	order	order	NOUN
cet-3935	14	3	to	to	PART
cet-3935	14	4	obtain	obtain	VERB
cet-3935	14	5	better	well	ADJ
cet-3935	14	6	reconstruction	reconstruction	NOUN
cet-3935	14	7	quality	quality	NOUN
cet-3935	14	8	,	,	PUNCT
cet-3935	14	9	many	many	ADJ
cet-3935	14	10	algorithms	algorithm	NOUN
cet-3935	14	11	have	have	AUX
cet-3935	14	12	been	be	AUX
cet-3935	14	13	proposed	propose	VERB
cet-3935	14	14	,	,	PUNCT
cet-3935	14	15	such	such	ADJ
cet-3935	14	16	as	as	ADP
cet-3935	14	17	greedy	greedy	ADJ
cet-3935	14	18	algorithm	algorithm	NOUN
cet-3935	14	19	(	(	PUNCT
cet-3935	14	20	sen	sen	PROPN
cet-3935	14	21	et	et	PROPN
cet-3935	14	22	al	al	PROPN
cet-3935	14	23	.	.	PROPN
cet-3935	14	24	,	,	PUNCT
cet-3935	14	25	2009	2009	NUM
cet-3935	14	26	)	)	PUNCT
cet-3935	14	27	,	,	PUNCT
cet-3935	14	28	convex	convex	NOUN
cet-3935	14	29	optimization	optimization	NOUN
cet-3935	14	30	algorithm	algorithm	NOUN
cet-3935	14	31	and	and	CCONJ
cet-3935	14	32	so	so	ADV
cet-3935	14	33	on	on	ADV
cet-3935	14	34	.	.	PUNCT
cet-3935	15	1	greedy	greedy	ADJ
cet-3935	15	2	algorithm	algorithm	NOUN
cet-3935	15	3	can	can	AUX
cet-3935	15	4	obtain	obtain	VERB
cet-3935	15	5	high	high	ADJ
cet-3935	15	6	computation	computation	NOUN
cet-3935	15	7	rate	rate	NOUN
cet-3935	15	8	,	,	PUNCT
cet-3935	15	9	such	such	ADJ
cet-3935	15	10	as	as	ADP
cet-3935	15	11	matching	matching	NOUN
cet-3935	15	12	pursuit	pursuit	NOUN
cet-3935	15	13	(	(	PUNCT
cet-3935	15	14	mp	mp	PROPN
cet-3935	15	15	)	)	PUNCT
cet-3935	15	16	(	(	PUNCT
cet-3935	15	17	mallat	mallat	PROPN
cet-3935	15	18	et	et	PROPN
cet-3935	15	19	al	al	PROPN
cet-3935	15	20	.	.	PROPN
cet-3935	15	21	,	,	PUNCT
cet-3935	15	22	1993	1993	NUM
cet-3935	15	23	)	)	PUNCT
cet-3935	15	24	and	and	CCONJ
cet-3935	15	25	matching	matching	NOUN
cet-3935	15	26	pursuit	pursuit	NOUN
cet-3935	15	27	orthogonal	orthogonal	NOUN
cet-3935	15	28	(	(	PUNCT
cet-3935	15	29	omp	omp	PROPN
cet-3935	15	30	)	)	PUNCT
cet-3935	15	31	(	(	PUNCT
cet-3935	15	32	pati	pati	PROPN
cet-3935	15	33	et	et	PROPN
cet-3935	15	34	al	al	PROPN
cet-3935	15	35	.	.	PROPN
cet-3935	15	36	,	,	PUNCT
cet-3935	15	37	1993	1993	NUM
cet-3935	15	38	)	)	PUNCT
cet-3935	16	1	algorithm	algorithm	NOUN
cet-3935	16	2	are	be	AUX
cet-3935	16	3	the	the	DET
cet-3935	16	4	most	most	ADV
cet-3935	16	5	widely	widely	ADV
cet-3935	16	6	used	use	VERB
cet-3935	16	7	.	.	PUNCT
cet-3935	17	1	compared	compare	VERB
cet-3935	17	2	with	with	ADP
cet-3935	17	3	the	the	DET
cet-3935	17	4	mp	mp	PROPN
cet-3935	17	5	algorithm	algorithm	NOUN
cet-3935	17	6	,	,	PUNCT
cet-3935	17	7	the	the	DET
cet-3935	17	8	omp	omp	PROPN
cet-3935	17	9	algorithm	algorithm	NOUN
cet-3935	17	10	is	be	AUX
cet-3935	17	11	based	base	VERB
cet-3935	17	12	on	on	ADP
cet-3935	17	13	the	the	DET
cet-3935	17	14	priors	prior	NOUN
cet-3935	17	15	of	of	ADP
cet-3935	17	16	the	the	DET
cet-3935	17	17	sparse	sparse	ADJ
cet-3935	17	18	degree	degree	NOUN
cet-3935	17	19	of	of	ADP
cet-3935	17	20	the	the	DET
cet-3935	17	21	signals	signal	NOUN
cet-3935	17	22	,	,	PUNCT
cet-3935	17	23	in	in	ADP
cet-3935	17	24	each	each	DET
cet-3935	17	25	iteration	iteration	NOUN
cet-3935	17	26	the	the	DET
cet-3935	17	27	selected	select	VERB
cet-3935	17	28	atoms	atom	NOUN
cet-3935	17	29	are	be	AUX
cet-3935	17	30	first	first	ADV
cet-3935	17	31	processed	process	VERB
cet-3935	17	32	by	by	ADP
cet-3935	17	33	schmidt	schmidt	PROPN
cet-3935	17	34	orthogonal	orthogonal	NOUN
cet-3935	17	35	,	,	PUNCT
cet-3935	17	36	and	and	CCONJ
cet-3935	17	37	the	the	DET
cet-3935	17	38	least	least	ADJ
cet-3935	17	39	square	square	ADJ
cet-3935	17	40	method	method	NOUN
cet-3935	17	41	is	be	AUX
cet-3935	17	42	introduced	introduce	VERB
cet-3935	17	43	,	,	PUNCT
cet-3935	17	44	so	so	CCONJ
cet-3935	17	45	the	the	DET
cet-3935	17	46	calculation	calculation	NOUN
cet-3935	17	47	is	be	AUX
cet-3935	17	48	more	more	ADV
cet-3935	17	49	accurate	accurate	ADJ
cet-3935	17	50	.	.	PUNCT
cet-3935	18	1	therefore	therefore	ADV
cet-3935	18	2	,	,	PUNCT
cet-3935	18	3	we	we	PRON
cet-3935	18	4	use	use	VERB
cet-3935	18	5	the	the	DET
cet-3935	18	6	omp	omp	PROPN
cet-3935	18	7	algorithm	algorithm	NOUN
cet-3935	18	8	for	for	ADP
cet-3935	18	9	reconstruction	reconstruction	NOUN
cet-3935	18	10	,	,	PUNCT
cet-3935	18	11	and	and	CCONJ
cet-3935	18	12	taking	take	VERB
cet-3935	18	13	into	into	ADP
cet-3935	18	14	account	account	NOUN
cet-3935	18	15	that	that	SCONJ
cet-3935	18	16	the	the	DET
cet-3935	18	17	wavelet	wavelet	NOUN
cet-3935	18	18	transform	transform	NOUN
cet-3935	18	19	can	can	AUX
cet-3935	18	20	obtain	obtain	VERB
cet-3935	18	21	the	the	DET
cet-3935	18	22	local	local	ADJ
cet-3935	18	23	characteristics	characteristic	NOUN
cet-3935	18	24	of	of	ADP
cet-3935	18	25	the	the	DET
cet-3935	18	26	signal	signal	NOUN
cet-3935	18	27	in	in	ADP
cet-3935	18	28	the	the	DET
cet-3935	18	29	time	time	NOUN
cet-3935	18	30	-	-	PUNCT
cet-3935	18	31	frequency	frequency	NOUN
cet-3935	18	32	domain	domain	NOUN
cet-3935	18	33	,	,	PUNCT
cet-3935	18	34	a	a	DET
cet-3935	18	35	video	video	NOUN
cet-3935	18	36	super	super	ADJ
cet-3935	18	37	resolution	resolution	NOUN
cet-3935	18	38	reconstruction	reconstruction	NOUN
cet-3935	18	39	method	method	NOUN
cet-3935	18	40	based	base	VERB
cet-3935	18	41	on	on	ADP
cet-3935	18	42	compressed	compressed	ADJ
cet-3935	18	43	sensing	sensing	NOUN
cet-3935	18	44	and	and	CCONJ
cet-3935	18	45	wavelet	wavelet	NOUN
cet-3935	18	46	transform	transform	NOUN
cet-3935	18	47	is	be	AUX
cet-3935	18	48	proposed	propose	VERB
cet-3935	18	49	.	.	PUNCT
cet-3935	19	1	firstly	firstly	ADV
cet-3935	19	2	,	,	PUNCT
cet-3935	19	3	the	the	DET
cet-3935	19	4	low	low	ADJ
cet-3935	19	5	resolution	resolution	NOUN
cet-3935	19	6	image	image	NOUN
cet-3935	19	7	is	be	AUX
cet-3935	19	8	decomposed	decompose	VERB
cet-3935	19	9	into	into	ADP
cet-3935	19	10	4	4	NUM
cet-3935	19	11	sub	sub	NOUN
cet-3935	19	12	bands	band	NOUN
cet-3935	19	13	by	by	ADP
cet-3935	19	14	wavelet	wavelet	NOUN
cet-3935	19	15	transform	transform	NOUN
cet-3935	19	16	,	,	PUNCT
cet-3935	19	17	then	then	ADV
cet-3935	19	18	cs	cs	PROPN
cet-3935	19	19	algorithm	algorithm	NOUN
cet-3935	19	20	is	be	AUX
cet-3935	19	21	used	use	VERB
cet-3935	19	22	to	to	PART
cet-3935	19	23	reconstruct	reconstruct	VERB
cet-3935	19	24	the	the	DET
cet-3935	19	25	image	image	NOUN
cet-3935	19	26	of	of	ADP
cet-3935	19	27	each	each	DET
cet-3935	19	28	sub	sub	NOUN
cet-3935	19	29	band	band	NOUN
cet-3935	19	30	.	.	PUNCT
cet-3935	20	1	finally	finally	ADV
cet-3935	20	2	,	,	PUNCT
cet-3935	20	3	the	the	DET
cet-3935	20	4	high	high	ADJ
cet-3935	20	5	resolution	resolution	NOUN
cet-3935	20	6	image	image	NOUN
cet-3935	20	7	is	be	AUX
cet-3935	20	8	reconstructed	reconstruct	VERB
cet-3935	20	9	by	by	ADP
cet-3935	20	10	wavelet	wavelet	NOUN
cet-3935	20	11	inverse	inverse	NOUN
cet-3935	20	12	transform	transform	NOUN
cet-3935	20	13	.	.	PUNCT
cet-3935	21	1	the	the	DET
cet-3935	21	2	experimental	experimental	ADJ
cet-3935	21	3	results	result	NOUN
cet-3935	21	4	confirm	confirm	VERB
cet-3935	21	5	the	the	DET
cet-3935	21	6	validity	validity	NOUN
cet-3935	21	7	and	and	CCONJ
cet-3935	21	8	practicability	practicability	NOUN
cet-3935	21	9	of	of	ADP
cet-3935	21	10	the	the	DET
cet-3935	21	11	algorithm	algorithm	NOUN
cet-3935	21	12	.	.	PUNCT
cet-3935	22	1	2	2	X
cet-3935	22	2	.	.	X
cet-3935	22	3	super	super	ADJ
cet-3935	22	4	-	-	ADJ
cet-3935	22	5	resolution	resolution	ADJ
cet-3935	22	6	reconstruction	reconstruction	NOUN
cet-3935	22	7	model	model	NOUN
cet-3935	22	8	the	the	DET
cet-3935	22	9	image	image	NOUN
cet-3935	22	10	super	super	NOUN
cet-3935	22	11	resolution	resolution	NOUN
cet-3935	22	12	observation	observation	NOUN
cet-3935	22	13	model	model	NOUN
cet-3935	22	14	generally	generally	ADV
cet-3935	22	15	can	can	AUX
cet-3935	22	16	be	be	AUX
cet-3935	22	17	expressed	express	VERB
cet-3935	22	18	as	as	ADP
cet-3935	22	19	:	:	PUNCT
cet-3935	22	20	y	y	PROPN
cet-3935	22	21	dbmx	dbmx	PROPN
cet-3935	22	22	n	n	PROPN
cet-3935	22	23			X
cet-3935	22	24	(	(	PUNCT
cet-3935	22	25	1	1	X
cet-3935	22	26	)	)	PUNCT
cet-3935	22	27	doi	doi	NOUN
cet-3935	22	28	:	:	PUNCT
cet-3935	22	29	10.3303	10.3303	NUM
cet-3935	22	30	/	/	SYM
cet-3935	22	31	cet1651071	cet1651071	NOUN
cet-3935	22	32	please	please	INTJ
cet-3935	22	33	cite	cite	VERB
cet-3935	22	34	this	this	DET
cet-3935	22	35	article	article	NOUN
cet-3935	22	36	as	as	ADP
cet-3935	22	37	:	:	PUNCT
cet-3935	22	38	tang	tang	PROPN
cet-3935	22	39	l.	l.	PROPN
cet-3935	22	40	,	,	PUNCT
cet-3935	22	41	song	song	PROPN
cet-3935	22	42	h.	h.	PROPN
cet-3935	22	43	,	,	PUNCT
cet-3935	22	44	chen	chen	PROPN
cet-3935	22	45	m.j	m.j	PROPN
cet-3935	22	46	.	.	PROPN
cet-3935	22	47	,	,	PUNCT
cet-3935	22	48	chen	chen	PROPN
cet-3935	22	49	y.m	y.m	PROPN
cet-3935	22	50	.	.	PROPN
cet-3935	22	51	,	,	PUNCT
cet-3935	22	52	2016	2016	NUM
cet-3935	22	53	,	,	PUNCT
cet-3935	22	54	a	a	DET
cet-3935	22	55	new	new	ADJ
cet-3935	22	56	video	video	NOUN
cet-3935	22	57	super	super	ADJ
cet-3935	22	58	-	-	ADJ
cet-3935	22	59	resolution	resolution	ADJ
cet-3935	22	60	reconstruction	reconstruction	NOUN
cet-3935	22	61	algorithm	algorithm	NOUN
cet-3935	22	62	based	base	VERB
cet-3935	22	63	on	on	ADP
cet-3935	22	64	compressive	compressive	ADJ
cet-3935	22	65	sensing	sensing	NOUN
cet-3935	22	66	,	,	PUNCT
cet-3935	22	67	chemical	chemical	ADJ
cet-3935	22	68	engineering	engineering	NOUN
cet-3935	22	69	transactions	transaction	NOUN
cet-3935	22	70	,	,	PUNCT
cet-3935	22	71	51	51	NUM
cet-3935	22	72	,	,	PUNCT
cet-3935	22	73	421	421	NUM
cet-3935	22	74	-	-	SYM
cet-3935	22	75	426	426	NUM
cet-3935	22	76	doi:10.3303	doi:10.3303	NOUN
cet-3935	22	77	/	/	SYM
cet-3935	22	78	cet1651071	cet1651071	NOUN
cet-3935	22	79	421	421	NUM
cet-3935	22	80	where	where	SCONJ
cet-3935	22	81	m	m	NOUN
cet-3935	22	82	is	be	AUX
cet-3935	22	83	the	the	DET
cet-3935	22	84	motion	motion	NOUN
cet-3935	22	85	operator	operator	NOUN
cet-3935	22	86	,	,	PUNCT
cet-3935	22	87	b	b	PROPN
cet-3935	22	88	is	be	AUX
cet-3935	22	89	the	the	DET
cet-3935	22	90	fuzzy	fuzzy	ADJ
cet-3935	22	91	matrix	matrix	NOUN
cet-3935	22	92	,	,	PUNCT
cet-3935	22	93	d	d	X
cet-3935	22	94	is	be	AUX
cet-3935	22	95	the	the	DET
cet-3935	22	96	down	down	ADJ
cet-3935	22	97	sampling	sample	VERB
cet-3935	22	98	operator	operator	NOUN
cet-3935	22	99	,	,	PUNCT
cet-3935	22	100	and	and	CCONJ
cet-3935	22	101	n	n	PRON
cet-3935	22	102	is	be	AUX
cet-3935	22	103	the	the	DET
cet-3935	22	104	random	random	ADJ
cet-3935	22	105	additive	additive	ADJ
cet-3935	22	106	noise	noise	NOUN
cet-3935	22	107	.	.	PUNCT
cet-3935	23	1	the	the	DET
cet-3935	23	2	degradation	degradation	NOUN
cet-3935	23	3	process	process	NOUN
cet-3935	23	4	is	be	AUX
cet-3935	23	5	shown	show	VERB
cet-3935	23	6	in	in	ADP
cet-3935	23	7	figure	figure	NOUN
cet-3935	23	8	1	1	NUM
cet-3935	23	9	.	.	PUNCT
cet-3935	23	10	from	from	ADP
cet-3935	23	11	the	the	DET
cet-3935	23	12	formula	formula	NOUN
cet-3935	23	13	(	(	PUNCT
cet-3935	23	14	1	1	NUM
cet-3935	23	15	)	)	PUNCT
cet-3935	23	16	,	,	PUNCT
cet-3935	23	17	it	it	PRON
cet-3935	23	18	can	can	AUX
cet-3935	23	19	be	be	AUX
cet-3935	23	20	seen	see	VERB
cet-3935	23	21	that	that	SCONJ
cet-3935	23	22	the	the	DET
cet-3935	23	23	process	process	NOUN
cet-3935	23	24	of	of	ADP
cet-3935	23	25	sr	sr	PROPN
cet-3935	23	26	reconstruction	reconstruction	NOUN
cet-3935	23	27	is	be	AUX
cet-3935	23	28	an	an	DET
cet-3935	23	29	ill	ill	ADV
cet-3935	23	30	posed	pose	VERB
cet-3935	23	31	inverse	inverse	NOUN
cet-3935	23	32	problem	problem	NOUN
cet-3935	23	33	.	.	PUNCT
cet-3935	24	1	the	the	DET
cet-3935	24	2	solution	solution	NOUN
cet-3935	24	3	of	of	ADP
cet-3935	24	4	the	the	DET
cet-3935	24	5	reconstruction	reconstruction	NOUN
cet-3935	24	6	method	method	NOUN
cet-3935	24	7	is	be	AUX
cet-3935	24	8	dependent	dependent	ADJ
cet-3935	24	9	on	on	ADP
cet-3935	24	10	the	the	DET
cet-3935	24	11	different	different	ADJ
cet-3935	24	12	prior	prior	ADJ
cet-3935	24	13	knowledge	knowledge	NOUN
cet-3935	24	14	,	,	PUNCT
cet-3935	24	15	which	which	PRON
cet-3935	24	16	influences	influence	VERB
cet-3935	24	17	and	and	CCONJ
cet-3935	24	18	limits	limit	VERB
cet-3935	24	19	the	the	DET
cet-3935	24	20	reconstruction	reconstruction	NOUN
cet-3935	24	21	results	result	NOUN
cet-3935	24	22	.	.	PUNCT
cet-3935	25	1	in	in	ADP
cet-3935	25	2	this	this	DET
cet-3935	25	3	paper	paper	NOUN
cet-3935	25	4	,	,	PUNCT
cet-3935	25	5	the	the	DET
cet-3935	25	6	sparse	sparse	ADJ
cet-3935	25	7	representation	representation	NOUN
cet-3935	25	8	model	model	NOUN
cet-3935	25	9	based	base	VERB
cet-3935	25	10	on	on	ADP
cet-3935	25	11	compressed	compressed	ADJ
cet-3935	25	12	sensing	sense	VERB
cet-3935	25	13	theory	theory	NOUN
cet-3935	25	14	is	be	AUX
cet-3935	25	15	used	use	VERB
cet-3935	25	16	to	to	PART
cet-3935	25	17	solve	solve	VERB
cet-3935	25	18	the	the	DET
cet-3935	25	19	above	above	ADJ
cet-3935	25	20	problems	problem	NOUN
cet-3935	25	21	,	,	PUNCT
cet-3935	25	22	and	and	CCONJ
cet-3935	25	23	we	we	PRON
cet-3935	25	24	can	can	AUX
cet-3935	25	25	get	get	VERB
cet-3935	25	26	the	the	DET
cet-3935	25	27	only	only	ADJ
cet-3935	25	28	sparse	sparse	ADJ
cet-3935	25	29	solution	solution	NOUN
cet-3935	25	30	to	to	ADP
cet-3935	25	31	the	the	DET
cet-3935	25	32	formula	formula	NOUN
cet-3935	25	33	(	(	PUNCT
cet-3935	25	34	1	1	NUM
cet-3935	25	35	)	)	PUNCT
cet-3935	25	36	under	under	ADP
cet-3935	25	37	the	the	DET
cet-3935	25	38	specific	specific	ADJ
cet-3935	25	39	conditions	condition	NOUN
cet-3935	25	40	.	.	PUNCT
cet-3935	26	1	original	original	ADJ
cet-3935	26	2	hr	hr	NOUN
cet-3935	26	3	image	image	NOUN
cet-3935	26	4	x	x	PUNCT
cet-3935	26	5	motion	motion	NOUN
cet-3935	26	6	mk	mk	NOUN
cet-3935	26	7	+	+	CCONJ
cet-3935	26	8	lr	lr	X
cet-3935	26	9	image	image	NOUN
cet-3935	26	10	yk	yk	PROPN
cet-3935	26	11	fuzzy	fuzzy	ADJ
cet-3935	26	12	psf	psf	NOUN
cet-3935	26	13	bk	bk	ADP
cet-3935	26	14	optical	optical	ADJ
cet-3935	26	15	blur	blur	NOUN
cet-3935	26	16	sensor	sensor	NOUN
cet-3935	26	17	blur	blur	PROPN
cet-3935	26	18	inter	inter	PROPN
cet-3935	26	19	frame	frame	NOUN
cet-3935	26	20	motion	motion	NOUN
cet-3935	26	21	blur	blur	NOUN
cet-3935	26	22	sampling	sample	VERB
cet-3935	26	23	dk	dk	PROPN
cet-3935	26	24	noise	noise	NOUN
cet-3935	26	25	nk	nk	PROPN
cet-3935	26	26	sr	sr	PROPN
cet-3935	26	27	reconstruction	reconstruction	NOUN
cet-3935	26	28	figure	figure	NOUN
cet-3935	26	29	1	1	NUM
cet-3935	26	30	:	:	PUNCT
cet-3935	26	31	observation	observation	NOUN
cet-3935	26	32	model	model	NOUN
cet-3935	26	33	3	3	X
cet-3935	26	34	.	.	PUNCT
cet-3935	26	35	compressive	compressive	ADJ
cet-3935	26	36	sensing	sense	VERB
cet-3935	26	37	theory	theory	NOUN
cet-3935	26	38	compressed	compress	VERB
cet-3935	26	39	sensing	sense	VERB
cet-3935	26	40	is	be	AUX
cet-3935	26	41	a	a	DET
cet-3935	26	42	new	new	ADJ
cet-3935	26	43	framework	framework	NOUN
cet-3935	26	44	different	different	ADJ
cet-3935	26	45	from	from	ADP
cet-3935	26	46	the	the	DET
cet-3935	26	47	traditional	traditional	ADJ
cet-3935	26	48	signal	signal	NOUN
cet-3935	26	49	compression	compression	NOUN
cet-3935	26	50	sampling	sample	VERB
cet-3935	26	51	.	.	PUNCT
cet-3935	27	1	the	the	DET
cet-3935	27	2	sampling	sampling	NOUN
cet-3935	27	3	and	and	CCONJ
cet-3935	27	4	compression	compression	NOUN
cet-3935	27	5	are	be	AUX
cet-3935	27	6	carried	carry	VERB
cet-3935	27	7	out	out	ADP
cet-3935	27	8	simultaneously	simultaneously	ADV
cet-3935	27	9	.	.	PUNCT
cet-3935	28	1	for	for	ADP
cet-3935	28	2	sparse	sparse	ADJ
cet-3935	28	3	expressed	express	VERB
cet-3935	28	4	or	or	CCONJ
cet-3935	28	5	compressed	compress	VERB
cet-3935	28	6	original	original	ADJ
cet-3935	28	7	signal	signal	NOUN
cet-3935	28	8	,	,	PUNCT
cet-3935	28	9	through	through	ADP
cet-3935	28	10	the	the	DET
cet-3935	28	11	sparse	sparse	ADJ
cet-3935	28	12	transform	transform	VERB
cet-3935	28	13	the	the	DET
cet-3935	28	14	original	original	ADJ
cet-3935	28	15	signal	signal	NOUN
cet-3935	28	16	can	can	AUX
cet-3935	28	17	be	be	AUX
cet-3935	28	18	accurately	accurately	ADV
cet-3935	28	19	reconstructed	reconstruct	VERB
cet-3935	28	20	with	with	ADP
cet-3935	28	21	a	a	DET
cet-3935	28	22	little	little	ADJ
cet-3935	28	23	sampling	sample	VERB
cet-3935	28	24	values	value	NOUN
cet-3935	28	25	that	that	PRON
cet-3935	28	26	meet	meet	VERB
cet-3935	28	27	certain	certain	ADJ
cet-3935	28	28	conditions	condition	NOUN
cet-3935	28	29	.	.	PUNCT
cet-3935	29	1	so	so	ADV
cet-3935	29	2	as	as	SCONJ
cet-3935	29	3	to	to	PART
cet-3935	29	4	save	save	VERB
cet-3935	29	5	a	a	DET
cet-3935	29	6	lot	lot	NOUN
cet-3935	29	7	of	of	ADP
cet-3935	29	8	sampling	sample	VERB
cet-3935	29	9	resources	resource	NOUN
cet-3935	29	10	,	,	PUNCT
cet-3935	29	11	operation	operation	NOUN
cet-3935	29	12	resources	resource	NOUN
cet-3935	29	13	and	and	CCONJ
cet-3935	29	14	storage	storage	NOUN
cet-3935	29	15	resources	resource	NOUN
cet-3935	29	16	,	,	PUNCT
cet-3935	29	17	the	the	DET
cet-3935	29	18	process	process	NOUN
cet-3935	29	19	is	be	AUX
cet-3935	29	20	shown	show	VERB
cet-3935	29	21	in	in	ADP
cet-3935	29	22	figure	figure	NOUN
cet-3935	29	23	2	2	NUM
cet-3935	29	24	.	.	PUNCT
cet-3935	29	25	input	input	NOUN
cet-3935	29	26	signal	signal	NOUN
cet-3935	29	27	sparse	sparse	ADJ
cet-3935	29	28	transformation	transformation	NOUN
cet-3935	29	29	observation	observation	NOUN
cet-3935	29	30	projection	projection	NOUN
cet-3935	29	31	signal	signal	NOUN
cet-3935	29	32	reconstruction	reconstruction	NOUN
cet-3935	29	33	figure	figure	NOUN
cet-3935	29	34	2	2	NUM
cet-3935	29	35	:	:	PUNCT
cet-3935	29	36	diagram	diagram	NOUN
cet-3935	29	37	of	of	ADP
cet-3935	29	38	compressed	compressed	ADJ
cet-3935	29	39	sensing	sense	VERB
cet-3935	29	40	theory	theory	NOUN
cet-3935	29	41	assume	assume	VERB
cet-3935	29	42	one	one	NUM
cet-3935	29	43	discrete	discrete	ADJ
cet-3935	29	44	one	one	NUM
cet-3935	29	45	-	-	PUNCT
cet-3935	29	46	dimensional	dimensional	ADJ
cet-3935	29	47	real	real	ADJ
cet-3935	29	48	signal	signal	NOUN
cet-3935	29	49	nx	nx	PROPN
cet-3935	29	50	r	r	PROPN
cet-3935	29	51	,	,	PUNCT
cet-3935	29	52	do	do	VERB
cet-3935	29	53	the	the	DET
cet-3935	29	54	sparse	sparse	ADJ
cet-3935	29	55	transformation	transformation	NOUN
cet-3935	29	56	x	x	X
cet-3935	29	57	x	x	PROPN
cet-3935	29	58	,	,	PUNCT
cet-3935	29	59	where	where	SCONJ
cet-3935	29	60			NOUN
cet-3935	29	61	is	be	AUX
cet-3935	29	62	the	the	DET
cet-3935	29	63	transformation	transformation	NOUN
cet-3935	29	64	matrix	matrix	NOUN
cet-3935	29	65	,	,	PUNCT
cet-3935	29	66	x	x	X
cet-3935	29	67	is	be	AUX
cet-3935	29	68	the	the	DET
cet-3935	29	69	equivalent	equivalent	ADJ
cet-3935	29	70	representation	representation	NOUN
cet-3935	29	71	of	of	ADP
cet-3935	29	72	x	x	PRON
cet-3935	29	73	in	in	ADP
cet-3935	29	74	sparse	sparse	ADJ
cet-3935	29	75	domain	domain	NOUN
cet-3935	29	76	.	.	PUNCT
cet-3935	30	1	then	then	ADV
cet-3935	30	2	the	the	DET
cet-3935	30	3	linear	linear	ADJ
cet-3935	30	4	projection	projection	NOUN
cet-3935	30	5	is	be	AUX
cet-3935	30	6	used	use	VERB
cet-3935	30	7	to	to	ADP
cet-3935	30	8	the	the	DET
cet-3935	30	9	signal	signal	NOUN
cet-3935	30	10	with	with	ADP
cet-3935	30	11	the	the	DET
cet-3935	30	12	observation	observation	NOUN
cet-3935	30	13	matrix	matrix	NOUN
cet-3935	30	14			PROPN
cet-3935	30	15	uncorrelated	uncorrelate	VERB
cet-3935	30	16	to	to	ADP
cet-3935	30	17			PROPN
cet-3935	30	18	(	(	PUNCT
cet-3935	30	19	bo	bo	PROPN
cet-3935	30	20	et	et	PROPN
cet-3935	30	21	al	al	PROPN
cet-3935	30	22	.	.	PROPN
cet-3935	30	23	,	,	PUNCT
cet-3935	30	24	2013	2013	NUM
cet-3935	30	25	)	)	PUNCT
cet-3935	30	26	,	,	PUNCT
cet-3935	30	27	y	y	PROPN
cet-3935	30	28	x	x	X
cet-3935	30	29	ψx	ψx	PROPN
cet-3935	30	30	ax	ax	PROPN
cet-3935	30	31			PROPN
cet-3935	30	32			NOUN
cet-3935	30	33	(	(	PUNCT
cet-3935	30	34	2	2	X
cet-3935	30	35	)	)	PUNCT
cet-3935	30	36	we	we	PRON
cet-3935	30	37	get	get	VERB
cet-3935	30	38	the	the	DET
cet-3935	30	39	observed	observe	VERB
cet-3935	30	40	value	value	NOUN
cet-3935	30	41	m	m	VERB
cet-3935	30	42	y	y	PROPN
cet-3935	30	43	r	r	PROPN
cet-3935	30	44	(	(	PUNCT
cet-3935	30	45	m	m	NOUN
cet-3935	30	46	n	n	NOUN
cet-3935	30	47	)	)	PUNCT
cet-3935	30	48	,	,	PUNCT
cet-3935	30	49	where	where	SCONJ
cet-3935	30	50	a=	a=	NOUN
cet-3935	30	51	is	be	AUX
cet-3935	30	52	a	a	DET
cet-3935	30	53	compressed	compressed	ADJ
cet-3935	30	54	sensing	sense	VERB
cet-3935	30	55	operator	operator	NOUN
cet-3935	30	56	.	.	PUNCT
cet-3935	31	1	x	x	X
cet-3935	31	2	can	can	AUX
cet-3935	31	3	be	be	AUX
cet-3935	31	4	seen	see	VERB
cet-3935	31	5	as	as	ADP
cet-3935	31	6	the	the	DET
cet-3935	31	7	hr	hr	NOUN
cet-3935	31	8	image	image	NOUN
cet-3935	31	9	on	on	ADP
cet-3935	31	10	the	the	DET
cet-3935	31	11	sr	sr	PROPN
cet-3935	31	12	reconstruction	reconstruction	NOUN
cet-3935	31	13	,	,	PUNCT
cet-3935	31	14	y	y	PROPN
cet-3935	31	15	can	can	AUX
cet-3935	31	16	be	be	AUX
cet-3935	31	17	considered	consider	VERB
cet-3935	31	18	as	as	ADP
cet-3935	31	19	the	the	DET
cet-3935	31	20	input	input	NOUN
cet-3935	31	21	lr	lr	NOUN
cet-3935	31	22	images	image	NOUN
cet-3935	31	23	.	.	PUNCT
cet-3935	32	1	however	however	ADV
cet-3935	32	2	,	,	PUNCT
cet-3935	32	3	the	the	DET
cet-3935	32	4	formula	formula	NOUN
cet-3935	32	5	(	(	PUNCT
cet-3935	32	6	1	1	X
cet-3935	32	7	)	)	PUNCT
cet-3935	32	8	is	be	AUX
cet-3935	32	9	less	less	ADV
cet-3935	32	10	certain	certain	ADJ
cet-3935	32	11	,	,	PUNCT
cet-3935	32	12	and	and	CCONJ
cet-3935	32	13	there	there	PRON
cet-3935	32	14	are	be	VERB
cet-3935	32	15	many	many	ADJ
cet-3935	32	16	solutions	solution	NOUN
cet-3935	32	17	.	.	PUNCT
cet-3935	33	1	the	the	DET
cet-3935	33	2	cs	cs	PROPN
cet-3935	33	3	theory	theory	NOUN
cet-3935	33	4	can	can	AUX
cet-3935	33	5	be	be	AUX
cet-3935	33	6	used	use	VERB
cet-3935	33	7	to	to	PART
cet-3935	33	8	obtain	obtain	VERB
cet-3935	33	9	the	the	DET
cet-3935	33	10	unique	unique	ADJ
cet-3935	33	11	solution	solution	NOUN
cet-3935	33	12	with	with	ADP
cet-3935	33	13	using	use	VERB
cet-3935	33	14	the	the	DET
cet-3935	33	15	priors	prior	NOUN
cet-3935	33	16	of	of	ADP
cet-3935	33	17	the	the	DET
cet-3935	33	18	image	image	NOUN
cet-3935	33	19	sparse	sparse	ADJ
cet-3935	33	20	representation	representation	NOUN
cet-3935	33	21	which	which	PRON
cet-3935	33	22	of	of	ADP
cet-3935	33	23	the	the	DET
cet-3935	33	24	signal	signal	NOUN
cet-3935	33	25	x	x	X
cet-3935	33	26	in	in	ADP
cet-3935	33	27	the	the	DET
cet-3935	33	28	transform	transform	NOUN
cet-3935	33	29	domain	domain	NOUN
cet-3935	33	30	.	.	NOUN
cet-3935	33	31	but	but	CCONJ
cet-3935	33	32	the	the	DET
cet-3935	33	33	premise	premise	NOUN
cet-3935	33	34	is	be	AUX
cet-3935	33	35	that	that	SCONJ
cet-3935	33	36			PROPN
cet-3935	33	37	and	and	CCONJ
cet-3935	33	38			NOUN
cet-3935	33	39	is	be	AUX
cet-3935	33	40	not	not	PART
cet-3935	33	41	related	relate	VERB
cet-3935	33	42	,	,	PUNCT
cet-3935	33	43	which	which	PRON
cet-3935	33	44	meets	meet	VERB
cet-3935	33	45	the	the	DET
cet-3935	33	46	restricted	restricted	ADJ
cet-3935	33	47	isometry	isometry	NOUN
cet-3935	33	48	property(rip	property(rip	NOUN
cet-3935	33	49	)	)	PUNCT
cet-3935	33	50	(	(	PUNCT
cet-3935	33	51	donoho	donoho	NOUN
cet-3935	33	52	,	,	PUNCT
cet-3935	33	53	2006	2006	NUM
cet-3935	33	54	)	)	PUNCT
cet-3935	33	55	.	.	PUNCT
cet-3935	34	1	compressive	compressive	ADJ
cet-3935	34	2	sensing	sense	VERB
cet-3935	34	3	reconstruction	reconstruction	NOUN
cet-3935	34	4	is	be	AUX
cet-3935	34	5	to	to	PART
cet-3935	34	6	get	get	VERB
cet-3935	34	7	the	the	DET
cet-3935	34	8	sparsest	sparse	ADJ
cet-3935	34	9	representation	representation	NOUN
cet-3935	34	10	of	of	ADP
cet-3935	34	11	the	the	DET
cet-3935	34	12	signal	signal	NOUN
cet-3935	34	13	when	when	SCONJ
cet-3935	34	14	satisfying	satisfy	VERB
cet-3935	34	15	the	the	DET
cet-3935	34	16	observed	observed	ADJ
cet-3935	34	17	values	value	NOUN
cet-3935	34	18	,	,	PUNCT
cet-3935	34	19	it	it	PRON
cet-3935	34	20	can	can	AUX
cet-3935	34	21	be	be	AUX
cet-3935	34	22	solved	solve	VERB
cet-3935	34	23	by	by	ADP
cet-3935	34	24	the	the	DET
cet-3935	34	25	0	0	PROPN
cet-3935	34	26	optimization	optimization	NOUN
cet-3935	34	27	problem	problem	NOUN
cet-3935	34	28	:	:	PUNCT
cet-3935	35	1	0	0	NUM
cet-3935	35	2	min	min	NOUN
cet-3935	35	3	||	||	NOUN
cet-3935	35	4	||	||	PROPN
cet-3935	35	5	.	.	PUNCT
cet-3935	36	1	x	x	PUNCT
cet-3935	37	1	x	x	X
cet-3935	37	2	s	s	PROPN
cet-3935	37	3	t	t	X
cet-3935	37	4	y	y	PROPN
cet-3935	37	5	ax	ax	PROPN
cet-3935	37	6	(	(	PUNCT
cet-3935	37	7	3	3	NUM
cet-3935	37	8	)	)	PUNCT
cet-3935	37	9	where	where	SCONJ
cet-3935	37	10	0||	0||	PROPN
cet-3935	37	11	||x	||x	NOUN
cet-3935	37	12	expresses	express	VERB
cet-3935	37	13	the	the	DET
cet-3935	37	14	number	number	NOUN
cet-3935	37	15	of	of	ADP
cet-3935	37	16	nonzero	nonzero	ADJ
cet-3935	37	17	elements	element	NOUN
cet-3935	37	18	in	in	ADP
cet-3935	37	19	the	the	DET
cet-3935	37	20	variation	variation	NOUN
cet-3935	37	21	coefficient	coefficient	NOUN
cet-3935	37	22	x	x	X
cet-3935	37	23	.	.	PUNCT
cet-3935	38	1	due	due	ADP
cet-3935	38	2	to	to	ADP
cet-3935	38	3	the	the	DET
cet-3935	38	4	unstable	unstable	ADJ
cet-3935	38	5	solution	solution	NOUN
cet-3935	38	6	of	of	ADP
cet-3935	38	7	0	0	NOUN
cet-3935	38	8	norm	norm	NOUN
cet-3935	38	9	,	,	PUNCT
cet-3935	38	10	but	but	CCONJ
cet-3935	38	11	the	the	DET
cet-3935	38	12	same	same	ADJ
cet-3935	38	13	solution	solution	NOUN
cet-3935	38	14	with	with	ADP
cet-3935	38	15	1	1	PROPN
cet-3935	38	16	norm	norm	NOUN
cet-3935	38	17	under	under	ADP
cet-3935	38	18	certain	certain	ADJ
cet-3935	38	19	conditions	condition	NOUN
cet-3935	38	20	.	.	PUNCT
cet-3935	39	1	so	so	ADV
cet-3935	39	2	in	in	ADP
cet-3935	39	3	this	this	DET
cet-3935	39	4	paper	paper	NOUN
cet-3935	39	5	,	,	PUNCT
cet-3935	39	6	we	we	PRON
cet-3935	39	7	use	use	VERB
cet-3935	39	8	1	1	PROPN
cet-3935	39	9	norm	norm	NOUN
cet-3935	39	10	to	to	PART
cet-3935	39	11	solve	solve	VERB
cet-3935	39	12	the	the	DET
cet-3935	39	13	above	above	ADJ
cet-3935	39	14	optimization	optimization	NOUN
cet-3935	39	15	problem	problem	NOUN
cet-3935	39	16	,	,	PUNCT
cet-3935	39	17	that	that	PRON
cet-3935	39	18	is	be	AUX
cet-3935	39	19	1	1	NUM
cet-3935	39	20	min	min	NOUN
cet-3935	39	21	||	||	NOUN
cet-3935	39	22	||	||	PROPN
cet-3935	39	23	.	.	PUNCT
cet-3935	40	1	x	x	PUNCT
cet-3935	40	2	x	x	X
cet-3935	40	3	s	s	PROPN
cet-3935	40	4	t	t	X
cet-3935	40	5	y	y	PROPN
cet-3935	40	6	ax	ax	PROPN
cet-3935	40	7	(	(	PUNCT
cet-3935	40	8	4	4	X
cet-3935	40	9	)	)	PUNCT
cet-3935	40	10	it	it	PRON
cet-3935	40	11	is	be	AUX
cet-3935	40	12	transformed	transform	VERB
cet-3935	40	13	into	into	ADP
cet-3935	40	14	a	a	DET
cet-3935	40	15	convex	convex	ADJ
cet-3935	40	16	optimization	optimization	NOUN
cet-3935	40	17	problem	problem	NOUN
cet-3935	40	18	,	,	PUNCT
cet-3935	40	19	thus	thus	ADV
cet-3935	40	20	the	the	DET
cet-3935	40	21	linear	linear	ADJ
cet-3935	40	22	programming	programming	NOUN
cet-3935	40	23	can	can	AUX
cet-3935	40	24	be	be	AUX
cet-3935	40	25	used	use	VERB
cet-3935	40	26	to	to	PART
cet-3935	40	27	solve	solve	VERB
cet-3935	40	28	.	.	PUNCT
cet-3935	41	1	422	422	NUM
cet-3935	41	2	4	4	NUM
cet-3935	41	3	.	.	PUNCT
cet-3935	41	4	super	super	ADJ
cet-3935	41	5	resolution	resolution	NOUN
cet-3935	41	6	reconstruction	reconstruction	NOUN
cet-3935	41	7	based	base	VERB
cet-3935	41	8	on	on	ADP
cet-3935	41	9	the	the	DET
cet-3935	41	10	wavelet	wavelet	NOUN
cet-3935	41	11	transform	transform	NOUN
cet-3935	41	12	wavelet	wavelet	NOUN
cet-3935	41	13	transform(wt	transform(wt	PROPN
cet-3935	41	14	)	)	PUNCT
cet-3935	41	15	can	can	AUX
cet-3935	41	16	decompose	decompose	VERB
cet-3935	41	17	the	the	DET
cet-3935	41	18	original	original	ADJ
cet-3935	41	19	signal	signal	NOUN
cet-3935	41	20	into	into	ADP
cet-3935	41	21	high	high	ADJ
cet-3935	41	22	frequency	frequency	NOUN
cet-3935	41	23	and	and	CCONJ
cet-3935	41	24	low	low	ADJ
cet-3935	41	25	frequency	frequency	NOUN
cet-3935	41	26	signal	signal	NOUN
cet-3935	41	27	.	.	PUNCT
cet-3935	42	1	the	the	DET
cet-3935	42	2	low	low	ADJ
cet-3935	42	3	frequency	frequency	NOUN
cet-3935	42	4	contains	contain	VERB
cet-3935	42	5	the	the	DET
cet-3935	42	6	main	main	ADJ
cet-3935	42	7	features	feature	NOUN
cet-3935	42	8	of	of	ADP
cet-3935	42	9	the	the	DET
cet-3935	42	10	signal	signal	NOUN
cet-3935	42	11	,	,	PUNCT
cet-3935	42	12	the	the	DET
cet-3935	42	13	high	high	ADJ
cet-3935	42	14	frequency	frequency	NOUN
cet-3935	42	15	component	component	NOUN
cet-3935	42	16	contains	contain	VERB
cet-3935	42	17	the	the	DET
cet-3935	42	18	characteristics	characteristic	NOUN
cet-3935	42	19	details	detail	NOUN
cet-3935	42	20	.	.	PUNCT
cet-3935	43	1	multiple	multiple	ADJ
cet-3935	43	2	low	low	ADJ
cet-3935	43	3	frequency	frequency	NOUN
cet-3935	43	4	signal	signal	NOUN
cet-3935	43	5	can	can	AUX
cet-3935	43	6	be	be	AUX
cet-3935	43	7	obtained	obtain	VERB
cet-3935	43	8	by	by	ADP
cet-3935	43	9	re	re	NOUN
cet-3935	43	10	decomposition	decomposition	NOUN
cet-3935	43	11	of	of	ADP
cet-3935	43	12	the	the	DET
cet-3935	43	13	low	low	ADJ
cet-3935	43	14	frequency	frequency	NOUN
cet-3935	43	15	,	,	PUNCT
cet-3935	43	16	so	so	SCONJ
cet-3935	43	17	as	as	SCONJ
cet-3935	43	18	to	to	PART
cet-3935	43	19	get	get	VERB
cet-3935	43	20	the	the	DET
cet-3935	43	21	characteristics	characteristic	NOUN
cet-3935	43	22	of	of	ADP
cet-3935	43	23	the	the	DET
cet-3935	43	24	original	original	ADJ
cet-3935	43	25	signal	signal	NOUN
cet-3935	43	26	.	.	PUNCT
cet-3935	44	1	in	in	ADP
cet-3935	44	2	the	the	DET
cet-3935	44	3	process	process	NOUN
cet-3935	44	4	of	of	ADP
cet-3935	44	5	image	image	NOUN
cet-3935	44	6	super	super	ADJ
cet-3935	44	7	resolution	resolution	NOUN
cet-3935	44	8	reconstruction	reconstruction	NOUN
cet-3935	44	9	,	,	PUNCT
cet-3935	44	10	the	the	DET
cet-3935	44	11	traditional	traditional	ADJ
cet-3935	44	12	methods	method	NOUN
cet-3935	44	13	to	to	PART
cet-3935	44	14	recover	recover	VERB
cet-3935	44	15	the	the	DET
cet-3935	44	16	lost	lose	VERB
cet-3935	44	17	high	high	ADJ
cet-3935	44	18	frequency	frequency	NOUN
cet-3935	44	19	information	information	NOUN
cet-3935	44	20	of	of	ADP
cet-3935	44	21	the	the	DET
cet-3935	44	22	image	image	NOUN
cet-3935	44	23	such	such	ADJ
cet-3935	44	24	as	as	ADP
cet-3935	44	25	interpolation	interpolation	NOUN
cet-3935	44	26	method	method	NOUN
cet-3935	44	27	will	will	AUX
cet-3935	44	28	bring	bring	VERB
cet-3935	44	29	the	the	DET
cet-3935	44	30	fuzzy	fuzzy	ADJ
cet-3935	44	31	edges	edge	NOUN
cet-3935	44	32	.	.	PUNCT
cet-3935	45	1	wavelet	wavelet	NOUN
cet-3935	45	2	transform	transform	NOUN
cet-3935	45	3	is	be	AUX
cet-3935	45	4	a	a	DET
cet-3935	45	5	technique	technique	NOUN
cet-3935	45	6	for	for	ADP
cet-3935	45	7	time	time	NOUN
cet-3935	45	8	-	-	PUNCT
cet-3935	45	9	frequency	frequency	NOUN
cet-3935	45	10	analysis	analysis	NOUN
cet-3935	45	11	,	,	PUNCT
cet-3935	45	12	which	which	PRON
cet-3935	45	13	is	be	AUX
cet-3935	45	14	widely	widely	ADV
cet-3935	45	15	used	use	VERB
cet-3935	45	16	in	in	ADP
cet-3935	45	17	image	image	NOUN
cet-3935	45	18	analysis	analysis	NOUN
cet-3935	45	19	.	.	PUNCT
cet-3935	46	1	on	on	ADP
cet-3935	46	2	the	the	DET
cet-3935	46	3	image	image	NOUN
cet-3935	46	4	sr	sr	PROPN
cet-3935	46	5	reconstruction	reconstruction	NOUN
cet-3935	46	6	based	base	VERB
cet-3935	46	7	on	on	ADP
cet-3935	46	8	wavelet	wavelet	NOUN
cet-3935	46	9	transform	transform	VERB
cet-3935	46	10	the	the	DET
cet-3935	46	11	acquisition	acquisition	NOUN
cet-3935	46	12	of	of	ADP
cet-3935	46	13	high	high	ADJ
cet-3935	46	14	and	and	CCONJ
cet-3935	46	15	low	low	ADJ
cet-3935	46	16	frequency	frequency	NOUN
cet-3935	46	17	sub	sub	NOUN
cet-3935	46	18	bands	band	NOUN
cet-3935	46	19	is	be	AUX
cet-3935	46	20	very	very	ADV
cet-3935	46	21	important	important	ADJ
cet-3935	46	22	,	,	PUNCT
cet-3935	46	23	in	in	ADP
cet-3935	46	24	practical	practical	ADJ
cet-3935	46	25	applications	application	NOUN
cet-3935	46	26	the	the	DET
cet-3935	46	27	high	high	ADJ
cet-3935	46	28	frequency	frequency	NOUN
cet-3935	46	29	sub	sub	NOUN
cet-3935	46	30	bands	band	NOUN
cet-3935	46	31	are	be	AUX
cet-3935	46	32	directional	directional	ADJ
cet-3935	46	33	,	,	PUNCT
cet-3935	46	34	the	the	DET
cet-3935	46	35	visual	visual	ADJ
cet-3935	46	36	effect	effect	NOUN
cet-3935	46	37	of	of	ADP
cet-3935	46	38	the	the	DET
cet-3935	46	39	reconstructed	reconstructed	ADJ
cet-3935	46	40	image	image	NOUN
cet-3935	46	41	with	with	ADP
cet-3935	46	42	using	use	VERB
cet-3935	46	43	interpolation	interpolation	NOUN
cet-3935	46	44	method	method	NOUN
cet-3935	46	45	to	to	PART
cet-3935	46	46	reconstruct	reconstruct	VERB
cet-3935	46	47	the	the	DET
cet-3935	46	48	high	high	ADJ
cet-3935	46	49	frequency	frequency	NOUN
cet-3935	46	50	sub	sub	NOUN
cet-3935	46	51	band	band	NOUN
cet-3935	46	52	for	for	ADP
cet-3935	46	53	wavelet	wavelet	NOUN
cet-3935	46	54	inverse	inverse	NOUN
cet-3935	46	55	transform	transform	NOUN
cet-3935	46	56	is	be	AUX
cet-3935	46	57	poor	poor	ADJ
cet-3935	46	58	,	,	PUNCT
cet-3935	46	59	and	and	CCONJ
cet-3935	46	60	the	the	DET
cet-3935	46	61	quality	quality	NOUN
cet-3935	46	62	is	be	AUX
cet-3935	46	63	also	also	ADV
cet-3935	46	64	low	low	ADJ
cet-3935	46	65	.	.	PUNCT
cet-3935	47	1	in	in	ADP
cet-3935	47	2	view	view	NOUN
cet-3935	47	3	of	of	ADP
cet-3935	47	4	the	the	DET
cet-3935	47	5	fact	fact	NOUN
cet-3935	47	6	that	that	SCONJ
cet-3935	47	7	cs	cs	PROPN
cet-3935	47	8	technology	technology	NOUN
cet-3935	47	9	can	can	AUX
cet-3935	47	10	be	be	AUX
cet-3935	47	11	realized	realize	VERB
cet-3935	47	12	in	in	ADP
cet-3935	47	13	smaller	small	ADJ
cet-3935	47	14	distortion	distortion	NOUN
cet-3935	47	15	on	on	ADP
cet-3935	47	16	the	the	DET
cet-3935	47	17	recovery	recovery	NOUN
cet-3935	47	18	of	of	ADP
cet-3935	47	19	the	the	DET
cet-3935	47	20	original	original	ADJ
cet-3935	47	21	signal	signal	NOUN
cet-3935	47	22	,	,	PUNCT
cet-3935	47	23	so	so	SCONJ
cet-3935	47	24	in	in	ADP
cet-3935	47	25	this	this	DET
cet-3935	47	26	paper	paper	NOUN
cet-3935	47	27	we	we	PRON
cet-3935	47	28	use	use	VERB
cet-3935	47	29	cs	cs	ADJ
cet-3935	47	30	technology	technology	NOUN
cet-3935	47	31	to	to	PART
cet-3935	47	32	reconstruct	reconstruct	VERB
cet-3935	47	33	the	the	DET
cet-3935	47	34	sub	sub	NOUN
cet-3935	47	35	band	band	NOUN
cet-3935	47	36	.	.	PUNCT
cet-3935	48	1	assuming	assume	VERB
cet-3935	48	2	a	a	DET
cet-3935	48	3	low	low	ADJ
cet-3935	48	4	resolution	resolution	NOUN
cet-3935	48	5	image	image	NOUN
cet-3935	48	6	of	of	ADP
cet-3935	48	7	the	the	DET
cet-3935	48	8	size	size	NOUN
cet-3935	48	9	mn	mn	PRON
cet-3935	48	10	,	,	PUNCT
cet-3935	48	11	the	the	DET
cet-3935	48	12	process	process	NOUN
cet-3935	48	13	of	of	ADP
cet-3935	48	14	the	the	DET
cet-3935	48	15	sr	sr	PROPN
cet-3935	48	16	reconstruction	reconstruction	NOUN
cet-3935	48	17	algorithm	algorithm	NOUN
cet-3935	48	18	based	base	VERB
cet-3935	48	19	on	on	ADP
cet-3935	48	20	the	the	DET
cet-3935	48	21	wt	wt	NOUN
cet-3935	48	22	is	be	AUX
cet-3935	48	23	expressed	express	VERB
cet-3935	48	24	as	as	SCONJ
cet-3935	48	25	follows	follow	VERB
cet-3935	48	26	(	(	PUNCT
cet-3935	48	27	zuo	zuo	PROPN
cet-3935	48	28	et	et	PROPN
cet-3935	48	29	al	al	PROPN
cet-3935	48	30	.	.	PROPN
cet-3935	48	31	,	,	PUNCT
cet-3935	48	32	2015	2015	NUM
cet-3935	48	33	):	):	PUNCT
cet-3935	48	34	1	1	X
cet-3935	48	35	)	)	PUNCT
cet-3935	48	36	decompose	decompose	VERB
cet-3935	48	37	the	the	DET
cet-3935	48	38	lr	lr	NOUN
cet-3935	48	39	image	image	NOUN
cet-3935	48	40	into	into	ADP
cet-3935	48	41	4	4	NUM
cet-3935	48	42	sub	sub	NOUN
cet-3935	48	43	bands	band	NOUN
cet-3935	48	44	using	use	VERB
cet-3935	48	45	the	the	DET
cet-3935	48	46	wt	wt	NOUN
cet-3935	48	47	,	,	PUNCT
cet-3935	48	48	respectively	respectively	ADV
cet-3935	48	49	are	be	AUX
cet-3935	48	50	the	the	DET
cet-3935	48	51	low	low	ADJ
cet-3935	48	52	frequency	frequency	NOUN
cet-3935	48	53	sub	sub	NOUN
cet-3935	48	54	band	band	NOUN
cet-3935	48	55	ll	ll	NOUN
cet-3935	48	56	and	and	CCONJ
cet-3935	48	57	three	three	NUM
cet-3935	48	58	high	high	ADJ
cet-3935	48	59	-	-	PUNCT
cet-3935	48	60	frequency	frequency	NOUN
cet-3935	48	61	sub	sub	NOUN
cet-3935	48	62	bands	band	NOUN
cet-3935	48	63	hh	hh	PROPN
cet-3935	48	64	,	,	PUNCT
cet-3935	48	65	lh	lh	PROPN
cet-3935	48	66	,	,	PUNCT
cet-3935	48	67	and	and	CCONJ
cet-3935	48	68	hl	hl	NOUN
cet-3935	48	69	,	,	PUNCT
cet-3935	48	70	corresponding	correspond	VERB
cet-3935	48	71	the	the	DET
cet-3935	48	72	horizontal	horizontal	ADJ
cet-3935	48	73	,	,	PUNCT
cet-3935	48	74	vertical	vertical	ADJ
cet-3935	48	75	and	and	CCONJ
cet-3935	48	76	diagonal	diagonal	ADJ
cet-3935	48	77	directions	direction	NOUN
cet-3935	48	78	,	,	PUNCT
cet-3935	48	79	as	as	SCONJ
cet-3935	48	80	shown	show	VERB
cet-3935	48	81	in	in	ADP
cet-3935	48	82	figure	figure	NOUN
cet-3935	48	83	3	3	NUM
cet-3935	48	84	;	;	PUNCT
cet-3935	48	85	2	2	NUM
cet-3935	48	86	)	)	PUNCT
cet-3935	48	87	decompose	decompose	VERB
cet-3935	48	88	the	the	DET
cet-3935	48	89	ll	ll	NOUN
cet-3935	48	90	with	with	ADP
cet-3935	48	91	the	the	DET
cet-3935	48	92	wt	wt	NOUN
cet-3935	48	93	again	again	ADV
cet-3935	48	94	,	,	PUNCT
cet-3935	48	95	we	we	PRON
cet-3935	48	96	can	can	AUX
cet-3935	48	97	get	get	VERB
cet-3935	48	98	4	4	NUM
cet-3935	48	99	sub	sub	NOUN
cet-3935	48	100	band	band	NOUN
cet-3935	48	101	images	image	NOUN
cet-3935	48	102	on	on	ADP
cet-3935	48	103	the	the	DET
cet-3935	48	104	next	next	ADJ
cet-3935	48	105	level	level	NOUN
cet-3935	48	106	;	;	PUNCT
cet-3935	48	107	3	3	X
cet-3935	48	108	)	)	PUNCT
cet-3935	48	109	reconstructed	reconstruct	VERB
cet-3935	48	110	the	the	DET
cet-3935	48	111	low	low	ADJ
cet-3935	48	112	frequency	frequency	NOUN
cet-3935	48	113	sub	sub	NOUN
cet-3935	48	114	band	band	NOUN
cet-3935	48	115	image	image	NOUN
cet-3935	48	116	by	by	ADP
cet-3935	48	117	using	use	VERB
cet-3935	48	118	the	the	DET
cet-3935	48	119	cs	cs	PROPN
cet-3935	48	120	technology	technology	NOUN
cet-3935	48	121	to	to	ADP
cet-3935	48	122	the	the	DET
cet-3935	48	123	low	low	ADJ
cet-3935	48	124	frequency	frequency	NOUN
cet-3935	48	125	sub	sub	NOUN
cet-3935	48	126	band	band	NOUN
cet-3935	48	127	;	;	PUNCT
cet-3935	48	128	4	4	X
cet-3935	48	129	)	)	PUNCT
cet-3935	48	130	reconstructed	reconstruct	VERB
cet-3935	48	131	the	the	DET
cet-3935	48	132	high	high	ADJ
cet-3935	48	133	frequency	frequency	NOUN
cet-3935	48	134	sub	sub	NOUN
cet-3935	48	135	bands	band	NOUN
cet-3935	48	136	images	image	NOUN
cet-3935	48	137	by	by	ADP
cet-3935	48	138	using	use	VERB
cet-3935	48	139	the	the	DET
cet-3935	48	140	cs	cs	PROPN
cet-3935	48	141	to	to	ADP
cet-3935	48	142	three	three	NUM
cet-3935	48	143	high	high	ADJ
cet-3935	48	144	frequency	frequency	NOUN
cet-3935	48	145	sub	sub	NOUN
cet-3935	48	146	bands	band	NOUN
cet-3935	48	147	;	;	PUNCT
cet-3935	48	148	5	5	X
cet-3935	48	149	)	)	PUNCT
cet-3935	48	150	using	use	VERB
cet-3935	48	151	wavelet	wavelet	NOUN
cet-3935	48	152	inverse	inverse	NOUN
cet-3935	48	153	transform	transform	NOUN
cet-3935	48	154	to	to	PART
cet-3935	48	155	reconstruct	reconstruct	VERB
cet-3935	48	156	the	the	DET
cet-3935	48	157	low	low	ADJ
cet-3935	48	158	frequency	frequency	NOUN
cet-3935	48	159	sub	sub	NOUN
cet-3935	48	160	band	band	NOUN
cet-3935	48	161	and	and	CCONJ
cet-3935	48	162	high	high	ADJ
cet-3935	48	163	frequency	frequency	NOUN
cet-3935	48	164	sub	sub	NOUN
cet-3935	48	165	,	,	PUNCT
cet-3935	48	166	so	so	SCONJ
cet-3935	48	167	as	as	SCONJ
cet-3935	48	168	to	to	PART
cet-3935	48	169	obtain	obtain	VERB
cet-3935	48	170	the	the	DET
cet-3935	48	171	reconstructed	reconstructed	ADJ
cet-3935	48	172	image	image	NOUN
cet-3935	48	173	.	.	PUNCT
cet-3935	49	1	figure	figure	VERB
cet-3935	49	2	3	3	NUM
cet-3935	49	3	:	:	PUNCT
cet-3935	49	4	pyramidal	pyramidal	ADJ
cet-3935	49	5	structure	structure	NOUN
cet-3935	49	6	5	5	NUM
cet-3935	49	7	.	.	NUM
cet-3935	49	8	compressed	compress	VERB
cet-3935	49	9	sensing	sensing	NOUN
cet-3935	49	10	applied	apply	VERB
cet-3935	49	11	to	to	ADP
cet-3935	49	12	the	the	DET
cet-3935	49	13	sr	sr	PROPN
cet-3935	49	14	reconstruction	reconstruction	NOUN
cet-3935	49	15	appling	apple	VERB
cet-3935	49	16	the	the	DET
cet-3935	49	17	cs	cs	PROPN
cet-3935	49	18	theory	theory	NOUN
cet-3935	49	19	in	in	ADP
cet-3935	49	20	super	super	ADJ
cet-3935	49	21	resolution	resolution	NOUN
cet-3935	49	22	reconstruction	reconstruction	NOUN
cet-3935	49	23	needs	need	VERB
cet-3935	49	24	to	to	PART
cet-3935	49	25	ensure	ensure	VERB
cet-3935	49	26	that	that	SCONJ
cet-3935	49	27	there	there	PRON
cet-3935	49	28	is	be	VERB
cet-3935	49	29	no	no	DET
cet-3935	49	30	correlation	correlation	NOUN
cet-3935	49	31	between	between	ADP
cet-3935	49	32	the	the	DET
cet-3935	49	33	observation	observation	NOUN
cet-3935	49	34	matrix	matrix	NOUN
cet-3935	49	35	and	and	CCONJ
cet-3935	49	36	sparse	sparse	ADJ
cet-3935	49	37	matrix	matrix	NOUN
cet-3935	49	38	.	.	PUNCT
cet-3935	50	1	so	so	ADV
cet-3935	50	2	we	we	PRON
cet-3935	50	3	need	need	VERB
cet-3935	50	4	a	a	DET
cet-3935	50	5	low	low	ADJ
cet-3935	50	6	pass	pass	NOUN
cet-3935	50	7	filter(lpf	filter(lpf	NOUN
cet-3935	50	8	)	)	PUNCT
cet-3935	50	9	for	for	ADP
cet-3935	50	10	pretreatment	pretreatment	NOUN
cet-3935	50	11	before	before	ADP
cet-3935	50	12	down	down	ADP
cet-3935	50	13	sampling	sample	VERB
cet-3935	50	14	the	the	DET
cet-3935	50	15	hr	hr	NOUN
cet-3935	50	16	image	image	NOUN
cet-3935	50	17	,	,	PUNCT
cet-3935	50	18	which	which	PRON
cet-3935	50	19	ensures	ensure	VERB
cet-3935	50	20	the	the	DET
cet-3935	50	21	un	un	NOUN
cet-3935	50	22	-	-	NOUN
cet-3935	50	23	correlation	correlation	NOUN
cet-3935	50	24	between	between	ADP
cet-3935	50	25	the	the	DET
cet-3935	50	26	sparse	sparse	ADJ
cet-3935	50	27	matrix	matrix	NOUN
cet-3935	50	28	and	and	CCONJ
cet-3935	50	29	observation	observation	NOUN
cet-3935	50	30	matrix	matrix	NOUN
cet-3935	50	31	after	after	ADP
cet-3935	50	32	the	the	DET
cet-3935	50	33	hr	hr	NOUN
cet-3935	50	34	image	image	NOUN
cet-3935	50	35	sampling	sample	VERB
cet-3935	50	36	.	.	PUNCT
cet-3935	51	1	consider	consider	VERB
cet-3935	51	2	the	the	DET
cet-3935	51	3	high	high	ADJ
cet-3935	51	4	resolution	resolution	NOUN
cet-3935	51	5	image	image	NOUN
cet-3935	51	6	is	be	AUX
cet-3935	51	7	x	x	X
cet-3935	51	8	,	,	PUNCT
cet-3935	51	9	obtain	obtain	VERB
cet-3935	51	10	the	the	DET
cet-3935	51	11	fuzzy	fuzzy	ADJ
cet-3935	51	12	representation	representation	NOUN
cet-3935	51	13	by	by	ADP
cet-3935	51	14	gauss	gauss	ADJ
cet-3935	51	15	low	low	ADJ
cet-3935	51	16	-	-	PUNCT
cet-3935	51	17	pass	pass	NOUN
cet-3935	51	18	filter	filter	NOUN
cet-3935	51	19	:	:	PUNCT
cet-3935	51	20	xk=x	xk=x	PROPN
cet-3935	51	21	,	,	PUNCT
cet-3935	51	22	where	where	SCONJ
cet-3935	51	23	=f	=f	AUX
cet-3935	51	24	h	h	NOUN
cet-3935	51	25	gf	gf	PROPN
cet-3935	51	26	,	,	PUNCT
cet-3935	51	27	down	down	ADP
cet-3935	51	28	sampling	sample	VERB
cet-3935	51	29	to	to	ADP
cet-3935	51	30	xh	xh	PROPN
cet-3935	51	31	,	,	PUNCT
cet-3935	51	32	then	then	ADV
cet-3935	52	1	=	=	PUNCT
cet-3935	52	2	h	h	NOUN
cet-3935	52	3	h	h	NOUN
cet-3935	52	4	x	x	PUNCT
cet-3935	52	5	x	x	SYM
cet-3935	52	6	f	f	X
cet-3935	52	7	gfxy	gfxy	NOUN
cet-3935	52	8			PROPN
cet-3935	52	9			X
cet-3935	52	10			X
cet-3935	52	11	(	(	PUNCT
cet-3935	52	12	5	5	NUM
cet-3935	52	13	)	)	PUNCT
cet-3935	52	14	where	where	SCONJ
cet-3935	52	15	f	f	PROPN
cet-3935	52	16	is	be	AUX
cet-3935	52	17	the	the	DET
cet-3935	52	18	fourier	fourier	NOUN
cet-3935	52	19	transform	transform	NOUN
cet-3935	52	20	matrix	matrix	NOUN
cet-3935	52	21	.	.	PUNCT
cet-3935	53	1	this	this	DET
cet-3935	53	2	filter	filter	NOUN
cet-3935	53	3	effectively	effectively	ADV
cet-3935	53	4	reduces	reduce	VERB
cet-3935	53	5	the	the	DET
cet-3935	53	6	correlation	correlation	NOUN
cet-3935	53	7	between	between	ADP
cet-3935	53	8	the	the	DET
cet-3935	53	9	sparse	sparse	ADJ
cet-3935	53	10	matrix	matrix	NOUN
cet-3935	53	11	and	and	CCONJ
cet-3935	53	12	observation	observation	NOUN
cet-3935	53	13	matrix	matrix	NOUN
cet-3935	53	14	,	,	PUNCT
cet-3935	53	15	the	the	DET
cet-3935	53	16	cs	cs	PROPN
cet-3935	53	17	theory	theory	NOUN
cet-3935	53	18	can	can	AUX
cet-3935	53	19	be	be	AUX
cet-3935	53	20	applied	apply	VERB
cet-3935	53	21	to	to	ADP
cet-3935	53	22	super	super	ADJ
cet-3935	53	23	resolution	resolution	NOUN
cet-3935	53	24	reconstruction	reconstruction	NOUN
cet-3935	53	25	.	.	PUNCT
cet-3935	54	1	the	the	DET
cet-3935	54	2	process	process	NOUN
cet-3935	54	3	can	can	AUX
cet-3935	54	4	also	also	ADV
cet-3935	54	5	be	be	AUX
cet-3935	54	6	regarded	regard	VERB
cet-3935	54	7	as	as	ADP
cet-3935	54	8	solving	solve	VERB
cet-3935	54	9	the	the	DET
cet-3935	54	10	optimization	optimization	NOUN
cet-3935	54	11	problem	problem	NOUN
cet-3935	54	12	with	with	ADP
cet-3935	54	13	no	no	DET
cet-3935	54	14	constraint	constraint	NOUN
cet-3935	54	15	:	:	PUNCT
cet-3935	54	16	1	1	NUM
cet-3935	54	17	min	min	NOUN
cet-3935	54	18	||	||	NOUN
cet-3935	54	19	||	||	PROPN
cet-3935	54	20	.	.	PUNCT
cet-3935	55	1	h	h	NOUN
cet-3935	56	1	x	x	PUNCT
cet-3935	56	2	x	x	X
cet-3935	56	3	s	s	PROPN
cet-3935	56	4	t	t	X
cet-3935	56	5	y	y	PROPN
cet-3935	56	6	f	f	PROPN
cet-3935	57	1	gf	gf	PROPN
cet-3935	57	2	x	x	PUNCT
cet-3935	58	1			PROPN
cet-3935	58	2			PROPN
cet-3935	58	3	(	(	PUNCT
cet-3935	58	4	6	6	NUM
cet-3935	58	5	)	)	PUNCT
cet-3935	58	6	omp	omp	PROPN
cet-3935	58	7	algorithm	algorithm	NOUN
cet-3935	58	8	is	be	AUX
cet-3935	58	9	a	a	DET
cet-3935	58	10	nonlinear	nonlinear	ADJ
cet-3935	58	11	adaptive	adaptive	ADJ
cet-3935	58	12	algorithm	algorithm	NOUN
cet-3935	58	13	developed	develop	VERB
cet-3935	58	14	on	on	ADP
cet-3935	58	15	the	the	DET
cet-3935	58	16	basis	basis	NOUN
cet-3935	58	17	of	of	ADP
cet-3935	58	18	mp	mp	PROPN
cet-3935	58	19	algorithm	algorithm	NOUN
cet-3935	58	20	,	,	PUNCT
cet-3935	58	21	the	the	DET
cet-3935	58	22	difference	difference	NOUN
cet-3935	58	23	between	between	ADP
cet-3935	58	24	them	they	PRON
cet-3935	58	25	is	be	AUX
cet-3935	58	26	that	that	SCONJ
cet-3935	58	27	in	in	ADP
cet-3935	58	28	each	each	DET
cet-3935	58	29	iteration	iteration	NOUN
cet-3935	58	30	,	,	PUNCT
cet-3935	58	31	the	the	DET
cet-3935	58	32	selected	select	VERB
cet-3935	58	33	atoms	atom	NOUN
cet-3935	58	34	are	be	AUX
cet-3935	58	35	processed	process	VERB
cet-3935	58	36	by	by	ADP
cet-3935	58	37	the	the	DET
cet-3935	58	38	schmidt	schmidt	PROPN
cet-3935	58	39	orthogonal	orthogonal	NOUN
cet-3935	58	40	.	.	PUNCT
cet-3935	59	1	the	the	DET
cet-3935	59	2	convergence	convergence	NOUN
cet-3935	59	3	rate	rate	NOUN
cet-3935	59	4	of	of	ADP
cet-3935	59	5	the	the	DET
cet-3935	59	6	algorithm	algorithm	NOUN
cet-3935	59	7	is	be	AUX
cet-3935	59	8	faster	fast	ADJ
cet-3935	59	9	and	and	CCONJ
cet-3935	59	10	it	it	PRON
cet-3935	59	11	has	have	VERB
cet-3935	59	12	higher	high	ADJ
cet-3935	59	13	accuracy	accuracy	NOUN
cet-3935	59	14	.	.	PUNCT
cet-3935	60	1	when	when	SCONJ
cet-3935	60	2	the	the	DET
cet-3935	60	3	iteration	iteration	NOUN
cet-3935	60	4	number	number	NOUN
cet-3935	60	5	is	be	AUX
cet-3935	60	6	sparse	sparse	ADJ
cet-3935	60	7	,	,	PUNCT
cet-3935	60	8	423	423	NUM
cet-3935	60	9	the	the	DET
cet-3935	60	10	iterative	iterative	NOUN
cet-3935	60	11	process	process	NOUN
cet-3935	60	12	is	be	AUX
cet-3935	60	13	stopped	stop	VERB
cet-3935	60	14	.	.	PUNCT
cet-3935	61	1	consider	consider	VERB
cet-3935	61	2	the	the	DET
cet-3935	61	3	input	input	NOUN
cet-3935	61	4	signal	signal	NOUN
cet-3935	61	5	is	be	AUX
cet-3935	61	6	n	n	ADV
cet-3935	61	7	x	x	NOUN
cet-3935	61	8	r	r	ADJ
cet-3935	61	9	,	,	PUNCT
cet-3935	61	10	sparse	sparse	ADJ
cet-3935	61	11	degree	degree	NOUN
cet-3935	61	12	is	be	AUX
cet-3935	61	13	k	k	PROPN
cet-3935	61	14	,	,	PUNCT
cet-3935	61	15	the	the	DET
cet-3935	61	16	observation	observation	NOUN
cet-3935	61	17	matrix	matrix	NOUN
cet-3935	61	18	is	be	AUX
cet-3935	61	19	m	m	PROPN
cet-3935	61	20	n	n	ADV
cet-3935	61	21	r	r	NOUN
cet-3935	61	22			NOUN
cet-3935	61	23			PROPN
cet-3935	61	24	,	,	PUNCT
cet-3935	61	25	the	the	DET
cet-3935	61	26	observed	observed	ADJ
cet-3935	61	27	vector	vector	NOUN
cet-3935	61	28	is	be	AUX
cet-3935	61	29	m	m	PROPN
cet-3935	61	30	y	y	PROPN
cet-3935	61	31	r	r	PROPN
cet-3935	61	32	,	,	PUNCT
cet-3935	61	33	the	the	DET
cet-3935	61	34	steps	step	NOUN
cet-3935	61	35	of	of	ADP
cet-3935	61	36	the	the	DET
cet-3935	61	37	algorithm	algorithm	NOUN
cet-3935	61	38	are	be	AUX
cet-3935	61	39	as	as	SCONJ
cet-3935	61	40	follows	follow	VERB
cet-3935	61	41	:	:	PUNCT
cet-3935	61	42	1	1	X
cet-3935	61	43	.	.	X
cet-3935	61	44	initialize	initialize	VERB
cet-3935	61	45	the	the	DET
cet-3935	61	46	reconstructed	reconstruct	VERB
cet-3935	61	47	signal	signal	NOUN
cet-3935	61	48	ˆ	ˆ	PUNCT
cet-3935	61	49	0x	0x	NOUN
cet-3935	61	50			NOUN
cet-3935	61	51	,	,	PUNCT
cet-3935	61	52	the	the	DET
cet-3935	61	53	residual	residual	ADJ
cet-3935	61	54	error	error	NOUN
cet-3935	61	55	is	be	AUX
cet-3935	61	56	0	0	NUM
cet-3935	61	57	r	r	NOUN
cet-3935	61	58	y	y	NOUN
cet-3935	61	59	,	,	PUNCT
cet-3935	61	60	the	the	DET
cet-3935	61	61	index	index	NOUN
cet-3935	61	62	set	set	VERB
cet-3935	61	63	is	be	AUX
cet-3935	61	64	0	0	NUM
cet-3935	61	65			ADJ
cet-3935	61	66			PROPN
cet-3935	61	67	,	,	PUNCT
cet-3935	61	68	and	and	CCONJ
cet-3935	61	69	the	the	DET
cet-3935	61	70	iteration	iteration	NOUN
cet-3935	61	71	number	number	NOUN
cet-3935	61	72	t	t	PROPN
cet-3935	61	73	=	=	NOUN
cet-3935	61	74	1	1	NUM
cet-3935	61	75	;	;	PUNCT
cet-3935	61	76	2	2	NUM
cet-3935	61	77	.	.	X
cet-3935	61	78	find	find	VERB
cet-3935	61	79	the	the	DET
cet-3935	61	80	maximum	maximum	ADJ
cet-3935	61	81	absolute	absolute	ADJ
cet-3935	61	82	value	value	NOUN
cet-3935	61	83	in	in	ADP
cet-3935	61	84	the	the	DET
cet-3935	61	85	inner	inner	ADJ
cet-3935	61	86	product	product	NOUN
cet-3935	61	87	of	of	ADP
cet-3935	61	88	the	the	DET
cet-3935	61	89	residual	residual	ADJ
cet-3935	61	90	error	error	NOUN
cet-3935	61	91	and	and	CCONJ
cet-3935	61	92	observation	observation	NOUN
cet-3935	61	93	matrix	matrix	NOUN
cet-3935	61	94	,	,	PUNCT
cet-3935	61	95	and	and	CCONJ
cet-3935	61	96	record	record	VERB
cet-3935	61	97	the	the	DET
cet-3935	61	98	corresponding	correspond	VERB
cet-3935	61	99	elements	element	NOUN
cet-3935	61	100	as	as	ADP
cet-3935	61	101	t	t	PROPN
cet-3935	61	102			NOUN
cet-3935	61	103	;	;	PUNCT
cet-3935	61	104	3	3	X
cet-3935	61	105	.	.	X
cet-3935	61	106	update	update	VERB
cet-3935	61	107	the	the	DET
cet-3935	61	108	index	index	NOUN
cet-3935	61	109	set	set	VERB
cet-3935	61	110	1	1	NUM
cet-3935	61	111	{	{	PUNCT
cet-3935	61	112	}	}	PUNCT
cet-3935	61	113	t	t	PROPN
cet-3935	61	114	t	t	PROPN
cet-3935	61	115	t	t	PROPN
cet-3935	61	116			ADJ
cet-3935	61	117			PROPN
cet-3935	61	118			NOUN
cet-3935	61	119			NOUN
cet-3935	61	120			NOUN
cet-3935	61	121			NOUN
cet-3935	61	122	,	,	PUNCT
cet-3935	61	123	reconstruct	reconstruct	VERB
cet-3935	61	124	the	the	DET
cet-3935	61	125	atomic	atomic	NOUN
cet-3935	61	126	set	set	NOUN
cet-3935	61	127	1	1	NUM
cet-3935	61	128	[	[	PUNCT
cet-3935	61	129	,	,	PUNCT
cet-3935	61	130	]	]	PUNCT
cet-3935	61	131	t	t	PROPN
cet-3935	61	132	t	t	PROPN
cet-3935	61	133	t	t	PROPN
cet-3935	61	134			ADJ
cet-3935	61	135			PROPN
cet-3935	61	136			NOUN
cet-3935	61	137			PROPN
cet-3935	61	138			NUM
cet-3935	62	1			NOUN
cet-3935	62	2	in	in	ADP
cet-3935	62	3	the	the	DET
cet-3935	62	4	observation	observation	NOUN
cet-3935	62	5	matrix	matrix	NOUN
cet-3935	62	6	;	;	PUNCT
cet-3935	62	7	4	4	X
cet-3935	62	8	.	.	X
cet-3935	63	1	using	use	VERB
cet-3935	63	2	the	the	DET
cet-3935	63	3	least	least	ADJ
cet-3935	63	4	square	square	ADJ
cet-3935	63	5	method	method	NOUN
cet-3935	63	6	to	to	PART
cet-3935	63	7	calculate	calculate	VERB
cet-3935	63	8	the	the	DET
cet-3935	63	9	reconstructed	reconstructed	ADJ
cet-3935	63	10	signal	signal	NOUN
cet-3935	63	11	2	2	NUM
cet-3935	63	12	1	1	NUM
cet-3935	63	13	2	2	NUM
cet-3935	63	14	ˆ	ˆ	NOUN
cet-3935	63	15	ˆarg	ˆarg	NOUN
cet-3935	63	16	min	min	NOUN
cet-3935	64	1	||	||	PROPN
cet-3935	64	2	||	||	PUNCT
cet-3935	65	1	i	i	PRON
cet-3935	65	2	t	t	NOUN
cet-3935	65	3	t	t	NOUN
cet-3935	66	1	x	x	PUNCT
cet-3935	66	2	y	y	PROPN
cet-3935	66	3	x	x	PUNCT
cet-3935	66	4			VERB
cet-3935	66	5			PRON
cet-3935	66	6			NOUN
cet-3935	66	7	,	,	PUNCT
cet-3935	66	8	and	and	CCONJ
cet-3935	66	9	update	update	VERB
cet-3935	66	10	the	the	DET
cet-3935	66	11	residual	residual	ADJ
cet-3935	66	12	error	error	NOUN
cet-3935	66	13	1	1	NUM
cet-3935	66	14	ˆ	ˆ	NOUN
cet-3935	66	15	t	t	PROPN
cet-3935	66	16	t	t	NOUN
cet-3935	67	1	t	t	NOUN
cet-3935	67	2	r	r	X
cet-3935	67	3	y	y	PROPN
cet-3935	67	4	x	x	PUNCT
cet-3935	67	5			VERB
cet-3935	67	6			PRON
cet-3935	67	7			NOUN
cet-3935	67	8	;	;	PUNCT
cet-3935	67	9	5	5	X
cet-3935	67	10	.	.	X
cet-3935	68	1	if	if	SCONJ
cet-3935	68	2	meet	meet	VERB
cet-3935	68	3	the	the	DET
cet-3935	68	4	iteration	iteration	NOUN
cet-3935	68	5	condition	condition	NOUN
cet-3935	68	6	,	,	PUNCT
cet-3935	68	7	output	output	NOUN
cet-3935	68	8	x̂	x̂	NUM
cet-3935	68	9	,	,	PUNCT
cet-3935	68	10	which	which	PRON
cet-3935	68	11	is	be	AUX
cet-3935	68	12	the	the	DET
cet-3935	68	13	reconstructed	reconstructed	ADJ
cet-3935	68	14	image	image	NOUN
cet-3935	68	15	,	,	PUNCT
cet-3935	68	16	otherwise	otherwise	ADV
cet-3935	68	17	return	return	VERB
cet-3935	68	18	to	to	PART
cet-3935	68	19	step	step	NOUN
cet-3935	68	20	2	2	NUM
cet-3935	68	21	.	.	NOUN
cet-3935	68	22	6	6	NUM
cet-3935	68	23	.	.	PUNCT
cet-3935	69	1	experiments	experiment	NOUN
cet-3935	69	2	and	and	CCONJ
cet-3935	69	3	analysis	analysis	NOUN
cet-3935	69	4	consider	consider	VERB
cet-3935	69	5	two	two	NUM
cet-3935	69	6	groups	group	NOUN
cet-3935	69	7	of	of	ADP
cet-3935	69	8	video	video	NOUN
cet-3935	69	9	image	image	NOUN
cet-3935	69	10	"	"	PUNCT
cet-3935	69	11	calendar	calendar	NOUN
cet-3935	69	12	"	"	PUNCT
cet-3935	69	13	,	,	PUNCT
cet-3935	69	14	"	"	PUNCT
cet-3935	69	15	cap	cap	NOUN
cet-3935	69	16	"	"	PUNCT
cet-3935	69	17	as	as	ADP
cet-3935	69	18	the	the	DET
cet-3935	69	19	original	original	ADJ
cet-3935	69	20	hr	hr	NOUN
cet-3935	69	21	images	image	NOUN
cet-3935	69	22	,	,	PUNCT
cet-3935	69	23	select	select	VERB
cet-3935	69	24	one	one	NUM
cet-3935	69	25	frame	frame	NOUN
cet-3935	69	26	in	in	ADP
cet-3935	69	27	each	each	DET
cet-3935	69	28	groups	group	NOUN
cet-3935	69	29	of	of	ADP
cet-3935	69	30	the	the	DET
cet-3935	69	31	images	image	NOUN
cet-3935	69	32	for	for	ADP
cet-3935	69	33	the	the	DET
cet-3935	69	34	space	space	NOUN
cet-3935	69	35	fuzzy	fuzzy	NOUN
cet-3935	69	36	of	of	ADP
cet-3935	69	37	the	the	DET
cet-3935	69	38	gauss	gauss	PROPN
cet-3935	69	39	point	point	NOUN
cet-3935	69	40	spread	spread	VERB
cet-3935	69	41	function	function	NOUN
cet-3935	69	42	with	with	ADP
cet-3935	69	43	the	the	DET
cet-3935	69	44	size	size	NOUN
cet-3935	69	45	of	of	ADP
cet-3935	69	46	7×7	7×7	NUM
cet-3935	69	47	and	and	CCONJ
cet-3935	69	48	the	the	DET
cet-3935	69	49	variance	variance	NOUN
cet-3935	69	50	of	of	ADP
cet-3935	69	51	0.5	0.5	NUM
cet-3935	69	52	,	,	PUNCT
cet-3935	69	53	and	and	CCONJ
cet-3935	69	54	2	2	NUM
cet-3935	69	55	times	time	NOUN
cet-3935	69	56	space	space	NOUN
cet-3935	69	57	sampling	sampling	NOUN
cet-3935	69	58	,	,	PUNCT
cet-3935	69	59	then	then	ADV
cet-3935	69	60	add	add	VERB
cet-3935	69	61	the	the	DET
cet-3935	69	62	random	random	ADJ
cet-3935	69	63	noise	noise	NOUN
cet-3935	69	64	with	with	ADP
cet-3935	69	65	snr	snr	NOUN
cet-3935	69	66	of	of	ADP
cet-3935	69	67	30db	30db	NOUN
cet-3935	69	68	,	,	PUNCT
cet-3935	69	69	to	to	PART
cet-3935	69	70	be	be	AUX
cet-3935	69	71	the	the	DET
cet-3935	69	72	lr	lr	NOUN
cet-3935	69	73	images	image	NOUN
cet-3935	69	74	observed	observe	VERB
cet-3935	69	75	.	.	PUNCT
cet-3935	70	1	the	the	DET
cet-3935	70	2	interpolation	interpolation	NOUN
cet-3935	70	3	method	method	NOUN
cet-3935	70	4	,	,	PUNCT
cet-3935	70	5	compressive	compressive	ADJ
cet-3935	70	6	sensing	sensing	NOUN
cet-3935	70	7	method	method	NOUN
cet-3935	70	8	and	and	CCONJ
cet-3935	70	9	the	the	DET
cet-3935	70	10	algorithm	algorithm	NOUN
cet-3935	70	11	proposed	propose	VERB
cet-3935	70	12	are	be	AUX
cet-3935	70	13	compared	compare	VERB
cet-3935	70	14	in	in	ADP
cet-3935	70	15	the	the	DET
cet-3935	70	16	experiments	experiment	NOUN
cet-3935	70	17	for	for	ADP
cet-3935	70	18	the	the	DET
cet-3935	70	19	comprehensive	comprehensive	ADJ
cet-3935	70	20	analysis	analysis	NOUN
cet-3935	70	21	on	on	ADP
cet-3935	70	22	the	the	DET
cet-3935	70	23	performance	performance	NOUN
cet-3935	70	24	of	of	ADP
cet-3935	70	25	reconstruction	reconstruction	NOUN
cet-3935	70	26	from	from	ADP
cet-3935	70	27	two	two	NUM
cet-3935	70	28	indexes	index	NOUN
cet-3935	70	29	of	of	ADP
cet-3935	70	30	subjective	subjective	ADJ
cet-3935	70	31	effect	effect	NOUN
cet-3935	70	32	and	and	CCONJ
cet-3935	70	33	objective	objective	ADJ
cet-3935	70	34	evaluation	evaluation	NOUN
cet-3935	70	35	.	.	PUNCT
cet-3935	71	1	experiment	experiment	NOUN
cet-3935	71	2	1	1	NUM
cet-3935	71	3	comparison	comparison	NOUN
cet-3935	71	4	of	of	ADP
cet-3935	71	5	the	the	DET
cet-3935	71	6	subjective	subjective	ADJ
cet-3935	71	7	effect	effect	NOUN
cet-3935	71	8	the	the	DET
cet-3935	71	9	reconstruction	reconstruction	NOUN
cet-3935	71	10	effects	effect	NOUN
cet-3935	71	11	of	of	ADP
cet-3935	71	12	the	the	DET
cet-3935	71	13	various	various	ADJ
cet-3935	71	14	methods	method	NOUN
cet-3935	71	15	are	be	AUX
cet-3935	71	16	shown	show	VERB
cet-3935	71	17	in	in	ADP
cet-3935	71	18	figure	figure	NOUN
cet-3935	71	19	4	4	NUM
cet-3935	71	20	.	.	PUNCT
cet-3935	72	1	it	it	PRON
cet-3935	72	2	can	can	AUX
cet-3935	72	3	be	be	AUX
cet-3935	72	4	seen	see	VERB
cet-3935	72	5	that	that	SCONJ
cet-3935	72	6	the	the	DET
cet-3935	72	7	interpolation	interpolation	NOUN
cet-3935	72	8	method	method	NOUN
cet-3935	72	9	is	be	AUX
cet-3935	72	10	the	the	DET
cet-3935	72	11	worst	bad	ADJ
cet-3935	72	12	with	with	ADP
cet-3935	72	13	loss	loss	NOUN
cet-3935	72	14	of	of	ADP
cet-3935	72	15	the	the	DET
cet-3935	72	16	image	image	NOUN
cet-3935	72	17	edge	edge	NOUN
cet-3935	72	18	details	detail	NOUN
cet-3935	72	19	and	and	CCONJ
cet-3935	72	20	the	the	DET
cet-3935	72	21	fuzzy	fuzzy	ADJ
cet-3935	72	22	image	image	NOUN
cet-3935	72	23	.	.	PUNCT
cet-3935	73	1	compared	compare	VERB
cet-3935	73	2	with	with	ADP
cet-3935	73	3	the	the	DET
cet-3935	73	4	interpolation	interpolation	NOUN
cet-3935	73	5	method	method	NOUN
cet-3935	73	6	,	,	PUNCT
cet-3935	73	7	the	the	DET
cet-3935	73	8	image	image	NOUN
cet-3935	73	9	effect	effect	NOUN
cet-3935	73	10	of	of	ADP
cet-3935	73	11	cs	cs	ADJ
cet-3935	73	12	reconstruction	reconstruction	NOUN
cet-3935	73	13	is	be	AUX
cet-3935	73	14	better	well	ADJ
cet-3935	73	15	,	,	PUNCT
cet-3935	73	16	but	but	CCONJ
cet-3935	73	17	the	the	DET
cet-3935	73	18	edge	edge	NOUN
cet-3935	73	19	of	of	ADP
cet-3935	73	20	the	the	DET
cet-3935	73	21	image	image	NOUN
cet-3935	73	22	is	be	AUX
cet-3935	73	23	still	still	ADV
cet-3935	73	24	relatively	relatively	ADV
cet-3935	73	25	vague	vague	ADJ
cet-3935	73	26	,	,	PUNCT
cet-3935	73	27	and	and	CCONJ
cet-3935	73	28	the	the	DET
cet-3935	73	29	local	local	ADJ
cet-3935	73	30	excessive	excessive	ADJ
cet-3935	73	31	is	be	AUX
cet-3935	73	32	not	not	PART
cet-3935	73	33	very	very	ADV
cet-3935	73	34	natural	natural	ADJ
cet-3935	73	35	.	.	PUNCT
cet-3935	74	1	the	the	DET
cet-3935	74	2	proposed	propose	VERB
cet-3935	74	3	algorithm	algorithm	NOUN
cet-3935	74	4	is	be	AUX
cet-3935	74	5	combined	combine	VERB
cet-3935	74	6	with	with	ADP
cet-3935	74	7	the	the	DET
cet-3935	74	8	wavelet	wavelet	NOUN
cet-3935	74	9	transform	transform	NOUN
cet-3935	74	10	based	base	VERB
cet-3935	74	11	on	on	ADP
cet-3935	74	12	cs	cs	PROPN
cet-3935	74	13	technology	technology	NOUN
cet-3935	74	14	,	,	PUNCT
cet-3935	74	15	the	the	DET
cet-3935	74	16	image	image	NOUN
cet-3935	74	17	edge	edge	NOUN
cet-3935	74	18	detail	detail	NOUN
cet-3935	74	19	information	information	NOUN
cet-3935	74	20	is	be	AUX
cet-3935	74	21	restored	restore	VERB
cet-3935	74	22	by	by	ADP
cet-3935	74	23	reconstructing	reconstruct	VERB
cet-3935	74	24	the	the	DET
cet-3935	74	25	high	high	ADJ
cet-3935	74	26	frequency	frequency	NOUN
cet-3935	74	27	sub	sub	NOUN
cet-3935	74	28	bands	band	NOUN
cet-3935	74	29	from	from	ADP
cet-3935	74	30	wavelet	wavelet	NOUN
cet-3935	74	31	transform	transform	NOUN
cet-3935	74	32	decomposition	decomposition	NOUN
cet-3935	74	33	,	,	PUNCT
cet-3935	74	34	and	and	CCONJ
cet-3935	74	35	the	the	DET
cet-3935	74	36	image	image	NOUN
cet-3935	74	37	reconstruction	reconstruction	NOUN
cet-3935	74	38	accuracy	accuracy	NOUN
cet-3935	74	39	is	be	AUX
cet-3935	74	40	also	also	ADV
cet-3935	74	41	improved	improve	VERB
cet-3935	74	42	.	.	PUNCT
cet-3935	75	1	the	the	DET
cet-3935	75	2	visual	visual	ADJ
cet-3935	75	3	effect	effect	NOUN
cet-3935	75	4	is	be	AUX
cet-3935	75	5	very	very	ADV
cet-3935	75	6	close	close	ADJ
cet-3935	75	7	to	to	ADP
cet-3935	75	8	the	the	DET
cet-3935	75	9	original	original	ADJ
cet-3935	75	10	image	image	NOUN
cet-3935	75	11	,	,	PUNCT
cet-3935	75	12	which	which	PRON
cet-3935	75	13	confirms	confirm	VERB
cet-3935	75	14	the	the	DET
cet-3935	75	15	superiority	superiority	NOUN
cet-3935	75	16	of	of	ADP
cet-3935	75	17	the	the	DET
cet-3935	75	18	new	new	ADJ
cet-3935	75	19	algorithm	algorithm	NOUN
cet-3935	75	20	.	.	PUNCT
cet-3935	76	1	(	(	PUNCT
cet-3935	76	2	a	a	X
cet-3935	76	3	)	)	PUNCT
cet-3935	76	4	original	original	ADJ
cet-3935	76	5	hr	hr	NOUN
cet-3935	76	6	(	(	PUNCT
cet-3935	76	7	b	b	NOUN
cet-3935	76	8	)	)	PUNCT
cet-3935	76	9	bilinear	bilinear	NOUN
cet-3935	76	10	interpolation	interpolation	NOUN
cet-3935	76	11	(	(	PUNCT
cet-3935	76	12	c	c	NOUN
cet-3935	76	13	)	)	PUNCT
cet-3935	76	14	compressive	compressive	ADJ
cet-3935	76	15	sensing	sensing	NOUN
cet-3935	76	16	(	(	PUNCT
cet-3935	76	17	d	d	X
cet-3935	76	18	)	)	PUNCT
cet-3935	76	19	the	the	DET
cet-3935	76	20	proposed	propose	VERB
cet-3935	76	21	method	method	NOUN
cet-3935	76	22	(	(	PUNCT
cet-3935	76	23	a	a	X
cet-3935	76	24	)	)	PUNCT
cet-3935	76	25	original	original	ADJ
cet-3935	76	26	hr	hr	NOUN
cet-3935	76	27	(	(	PUNCT
cet-3935	76	28	b	b	NOUN
cet-3935	76	29	)	)	PUNCT
cet-3935	76	30	bilinear	bilinear	NOUN
cet-3935	76	31	interpolation	interpolation	NOUN
cet-3935	76	32	(	(	PUNCT
cet-3935	76	33	c	c	NOUN
cet-3935	76	34	)	)	PUNCT
cet-3935	76	35	compressive	compressive	ADJ
cet-3935	76	36	sensing	sensing	NOUN
cet-3935	76	37	(	(	PUNCT
cet-3935	76	38	d	d	X
cet-3935	76	39	)	)	PUNCT
cet-3935	76	40	the	the	DET
cet-3935	76	41	proposed	propose	VERB
cet-3935	76	42	method	method	NOUN
cet-3935	76	43	figure	figure	NOUN
cet-3935	76	44	4	4	NUM
cet-3935	76	45	:	:	PUNCT
cet-3935	76	46	the	the	DET
cet-3935	76	47	results	result	NOUN
cet-3935	76	48	of	of	ADP
cet-3935	76	49	the	the	DET
cet-3935	76	50	image	image	NOUN
cet-3935	76	51	reconstruction	reconstruction	NOUN
cet-3935	76	52	424	424	NUM
cet-3935	76	53	experiment	experiment	NOUN
cet-3935	76	54	2	2	NUM
cet-3935	76	55	the	the	DET
cet-3935	76	56	objective	objective	ADJ
cet-3935	76	57	evaluation	evaluation	NOUN
cet-3935	76	58	results	result	NOUN
cet-3935	76	59	we	we	PRON
cet-3935	76	60	take	take	VERB
cet-3935	76	61	the	the	DET
cet-3935	76	62	peak	peak	NOUN
cet-3935	76	63	signal	signal	NOUN
cet-3935	76	64	-	-	PUNCT
cet-3935	76	65	to	to	ADP
cet-3935	76	66	-	-	PUNCT
cet-3935	76	67	noise	noise	NOUN
cet-3935	76	68	ratio	ratio	NOUN
cet-3935	76	69	psnr	psnr	NOUN
cet-3935	76	70	as	as	ADP
cet-3935	76	71	the	the	DET
cet-3935	76	72	objective	objective	ADJ
cet-3935	76	73	evaluation	evaluation	NOUN
cet-3935	76	74	of	of	ADP
cet-3935	76	75	the	the	DET
cet-3935	76	76	performance	performance	NOUN
cet-3935	76	77	.	.	PUNCT
cet-3935	77	1	2	2	NUM
cet-3935	77	2	2	2	NUM
cet-3935	77	3	0	0	NUM
cet-3935	77	4	1	1	NUM
cet-3935	77	5	[	[	PUNCT
cet-3935	77	6	]	]	X
cet-3935	77	7	255	255	NUM
cet-3935	77	8	10	10	NUM
cet-3935	77	9	lg	lg	NOUN
cet-3935	77	10	(	(	PUNCT
cet-3935	77	11	(	(	PUNCT
cet-3935	77	12	,	,	PUNCT
cet-3935	77	13	)	)	PUNCT
cet-3935	77	14	(	(	PUNCT
cet-3935	77	15	,	,	PUNCT
cet-3935	77	16	)	)	PUNCT
cet-3935	77	17	)	)	PUNCT
cet-3935	78	1	mn	mn	PROPN
cet-3935	79	1	n	n	PROPN
cet-3935	79	2	psnr	psnr	NOUN
cet-3935	79	3	m	m	VERB
cet-3935	79	4	n	n	ADV
cet-3935	80	1	i	i	NOUN
cet-3935	80	2	x	x	PROPN
cet-3935	80	3	y	y	VERB
cet-3935	80	4	i	i	NOUN
cet-3935	80	5	x	x	VERB
cet-3935	81	1	y	y	NOUN
cet-3935	81	2			NOUN
cet-3935	82	1			PROPN
cet-3935	82	2			PROPN
cet-3935	82	3			PROPN
cet-3935	82	4			PROPN
cet-3935	82	5			PROPN
cet-3935	82	6	where	where	SCONJ
cet-3935	82	7	,	,	PUNCT
cet-3935	82	8	m	m	VERB
cet-3935	82	9	and	and	CCONJ
cet-3935	82	10	n	n	PROPN
cet-3935	82	11	respectively	respectively	ADV
cet-3935	82	12	is	be	AUX
cet-3935	82	13	the	the	DET
cet-3935	82	14	size	size	NOUN
cet-3935	82	15	of	of	ADP
cet-3935	82	16	the	the	DET
cet-3935	82	17	image	image	NOUN
cet-3935	82	18	pixels	pixel	VERB
cet-3935	82	19	.	.	PUNCT
cet-3935	83	1	through	through	ADP
cet-3935	83	2	the	the	DET
cet-3935	83	3	reconstruction	reconstruction	NOUN
cet-3935	83	4	effect	effect	NOUN
cet-3935	83	5	in	in	ADP
cet-3935	83	6	different	different	ADJ
cet-3935	83	7	magnification	magnification	NOUN
cet-3935	83	8	,	,	PUNCT
cet-3935	83	9	the	the	DET
cet-3935	83	10	algorithm	algorithm	NOUN
cet-3935	83	11	proposed	propose	VERB
cet-3935	83	12	performs	perform	VERB
cet-3935	83	13	well	well	ADV
cet-3935	83	14	with	with	ADP
cet-3935	83	15	the	the	DET
cet-3935	83	16	highest	high	ADJ
cet-3935	83	17	psnr	psnr	NOUN
cet-3935	83	18	,	,	PUNCT
cet-3935	83	19	thus	thus	ADV
cet-3935	83	20	the	the	DET
cet-3935	83	21	bilinear	bilinear	NOUN
cet-3935	83	22	interpolation	interpolation	NOUN
cet-3935	83	23	is	be	AUX
cet-3935	83	24	the	the	DET
cet-3935	83	25	worst	bad	ADJ
cet-3935	83	26	,	,	PUNCT
cet-3935	83	27	as	as	SCONJ
cet-3935	83	28	shown	show	VERB
cet-3935	83	29	in	in	ADP
cet-3935	83	30	table	table	NOUN
cet-3935	83	31	1	1	NUM
cet-3935	83	32	.	.	PUNCT
cet-3935	84	1	but	but	CCONJ
cet-3935	84	2	with	with	ADP
cet-3935	84	3	the	the	DET
cet-3935	84	4	increase	increase	NOUN
cet-3935	84	5	of	of	ADP
cet-3935	84	6	the	the	DET
cet-3935	84	7	magnification	magnification	NOUN
cet-3935	84	8	the	the	DET
cet-3935	84	9	observations	observation	NOUN
cet-3935	84	10	is	be	AUX
cet-3935	84	11	less	less	ADJ
cet-3935	84	12	,	,	PUNCT
cet-3935	84	13	the	the	DET
cet-3935	84	14	reconstruction	reconstruction	NOUN
cet-3935	84	15	error	error	NOUN
cet-3935	84	16	will	will	AUX
cet-3935	84	17	increase	increase	VERB
cet-3935	84	18	,	,	PUNCT
cet-3935	84	19	the	the	DET
cet-3935	84	20	corresponding	correspond	VERB
cet-3935	84	21	psnr	psnr	NOUN
cet-3935	84	22	will	will	AUX
cet-3935	84	23	decrease	decrease	VERB
cet-3935	84	24	.	.	PUNCT
cet-3935	85	1	and	and	CCONJ
cet-3935	85	2	from	from	ADP
cet-3935	85	3	the	the	DET
cet-3935	85	4	simulation	simulation	NOUN
cet-3935	85	5	result	result	NOUN
cet-3935	85	6	shown	show	VERB
cet-3935	85	7	in	in	ADP
cet-3935	85	8	figure	figure	NOUN
cet-3935	85	9	5	5	NUM
cet-3935	85	10	,	,	PUNCT
cet-3935	85	11	with	with	ADP
cet-3935	85	12	the	the	DET
cet-3935	85	13	increase	increase	NOUN
cet-3935	85	14	of	of	ADP
cet-3935	85	15	the	the	DET
cet-3935	85	16	iterations	iteration	NOUN
cet-3935	85	17	the	the	DET
cet-3935	85	18	psnr	psnr	NOUN
cet-3935	85	19	of	of	ADP
cet-3935	85	20	two	two	NUM
cet-3935	85	21	kinds	kind	NOUN
cet-3935	85	22	of	of	ADP
cet-3935	85	23	algorithms	algorithm	NOUN
cet-3935	85	24	for	for	ADP
cet-3935	85	25	image	image	NOUN
cet-3935	85	26	reconstruction	reconstruction	NOUN
cet-3935	85	27	tends	tend	VERB
cet-3935	85	28	to	to	PART
cet-3935	85	29	be	be	AUX
cet-3935	85	30	stable	stable	ADJ
cet-3935	85	31	,	,	PUNCT
cet-3935	85	32	but	but	CCONJ
cet-3935	85	33	compared	compare	VERB
cet-3935	85	34	with	with	ADP
cet-3935	85	35	the	the	DET
cet-3935	85	36	cs	cs	PROPN
cet-3935	85	37	method	method	NOUN
cet-3935	85	38	,	,	PUNCT
cet-3935	85	39	the	the	DET
cet-3935	85	40	new	new	ADJ
cet-3935	85	41	algorithm	algorithm	NOUN
cet-3935	85	42	possesses	possess	VERB
cet-3935	85	43	higher	high	ADJ
cet-3935	85	44	result	result	NOUN
cet-3935	85	45	,	,	PUNCT
cet-3935	85	46	which	which	PRON
cet-3935	85	47	shows	show	VERB
cet-3935	85	48	the	the	DET
cet-3935	85	49	better	well	ADJ
cet-3935	85	50	quality	quality	NOUN
cet-3935	85	51	of	of	ADP
cet-3935	85	52	the	the	DET
cet-3935	85	53	reconstructed	reconstructed	ADJ
cet-3935	85	54	image	image	NOUN
cet-3935	85	55	.	.	PUNCT
cet-3935	86	1	table	table	NOUN
cet-3935	86	2	1	1	NUM
cet-3935	86	3	:	:	PUNCT
cet-3935	86	4	comparison	comparison	NOUN
cet-3935	86	5	of	of	ADP
cet-3935	86	6	psnr	psnr	NOUN
cet-3935	86	7	in	in	ADP
cet-3935	86	8	the	the	DET
cet-3935	86	9	different	different	ADJ
cet-3935	86	10	magnification	magnification	NOUN
cet-3935	86	11	algorithms	algorithm	NOUN
cet-3935	86	12	magnification	magnification	VERB
cet-3935	86	13	2	2	NUM
cet-3935	86	14	3	3	NUM
cet-3935	86	15	4	4	NUM
cet-3935	86	16	5	5	NUM
cet-3935	86	17	6	6	NUM
cet-3935	86	18	7	7	NUM
cet-3935	86	19	bilinear	bilinear	NOUN
cet-3935	86	20	interpolation	interpolation	NOUN
cet-3935	86	21	27.56	27.56	NUM
cet-3935	86	22	26.05	26.05	NUM
cet-3935	86	23	23.93	23.93	NUM
cet-3935	86	24	21.22	21.22	NUM
cet-3935	86	25	18.31	18.31	NUM
cet-3935	86	26	17.57	17.57	NUM
cet-3935	86	27	compressive	compressive	NOUN
cet-3935	86	28	sensing	sense	VERB
cet-3935	86	29	28.89	28.89	NUM
cet-3935	86	30	27.74	27.74	NUM
cet-3935	86	31	24.07	24.07	NUM
cet-3935	86	32	21.56	21.56	NUM
cet-3935	86	33	19.45	19.45	NUM
cet-3935	86	34	18.08	18.08	NUM
cet-3935	86	35	the	the	DET
cet-3935	86	36	proposed	propose	VERB
cet-3935	86	37	30.81	30.81	NUM
cet-3935	86	38	29.22	29.22	NUM
cet-3935	86	39	27.14	27.14	NUM
cet-3935	86	40	26.56	26.56	NUM
cet-3935	86	41	25.09	25.09	NUM
cet-3935	86	42	23.74	23.74	NUM
cet-3935	86	43	0	0	NUM
cet-3935	86	44	5	5	NUM
cet-3935	86	45	10	10	NUM
cet-3935	86	46	15	15	NUM
cet-3935	86	47	20	20	NUM
cet-3935	86	48	25	25	NUM
cet-3935	86	49	30	30	NUM
cet-3935	86	50	16	16	NUM
cet-3935	86	51	18	18	NUM
cet-3935	86	52	20	20	NUM
cet-3935	86	53	22	22	NUM
cet-3935	86	54	24	24	NUM
cet-3935	86	55	26	26	NUM
cet-3935	86	56	28	28	NUM
cet-3935	86	57	30	30	NUM
cet-3935	86	58	iterations	iteration	NOUN
cet-3935	87	1	p	p	X
cet-3935	87	2	s	s	NOUN
cet-3935	87	3	n	n	PRON
cet-3935	87	4	r	r	NOUN
cet-3935	87	5	/d	/d	PUNCT
cet-3935	87	6	b	b	NOUN
cet-3935	87	7	compressive	compressive	ADJ
cet-3935	87	8	sensing	sense	VERB
cet-3935	87	9	the	the	DET
cet-3935	87	10	proposed	propose	VERB
cet-3935	87	11	algorithm	algorithm	NOUN
cet-3935	87	12	figure	figure	NOUN
cet-3935	87	13	5	5	NUM
cet-3935	87	14	:	:	PUNCT
cet-3935	87	15	psnr	psnr	NOUN
cet-3935	87	16	changes	change	NOUN
cet-3935	87	17	with	with	ADP
cet-3935	87	18	the	the	DET
cet-3935	87	19	different	different	ADJ
cet-3935	87	20	iterations	iteration	NOUN
cet-3935	87	21	7	7	NUM
cet-3935	87	22	.	.	PUNCT
cet-3935	87	23	conclusions	conclusion	NOUN
cet-3935	87	24	in	in	ADP
cet-3935	87	25	this	this	DET
cet-3935	87	26	paper	paper	NOUN
cet-3935	87	27	the	the	DET
cet-3935	87	28	theory	theory	NOUN
cet-3935	87	29	of	of	ADP
cet-3935	87	30	compressed	compressed	ADJ
cet-3935	87	31	sensing	sensing	NOUN
cet-3935	87	32	is	be	AUX
cet-3935	87	33	applied	apply	VERB
cet-3935	87	34	into	into	ADP
cet-3935	87	35	the	the	DET
cet-3935	87	36	video	video	NOUN
cet-3935	87	37	super	super	ADJ
cet-3935	87	38	-	-	ADJ
cet-3935	87	39	resolution	resolution	ADJ
cet-3935	87	40	reconstruction	reconstruction	NOUN
cet-3935	87	41	,	,	PUNCT
cet-3935	87	42	in	in	ADP
cet-3935	87	43	order	order	NOUN
cet-3935	87	44	to	to	PART
cet-3935	87	45	improve	improve	VERB
cet-3935	87	46	the	the	DET
cet-3935	87	47	reconstruction	reconstruction	NOUN
cet-3935	87	48	accuracy	accuracy	NOUN
cet-3935	87	49	,	,	PUNCT
cet-3935	87	50	the	the	DET
cet-3935	87	51	method	method	NOUN
cet-3935	87	52	combined	combine	VERB
cet-3935	87	53	with	with	ADP
cet-3935	87	54	wavelet	wavelet	NOUN
cet-3935	87	55	transform	transform	NOUN
cet-3935	87	56	and	and	CCONJ
cet-3935	87	57	compressed	compressed	ADJ
cet-3935	87	58	sensing	sensing	NOUN
cet-3935	87	59	is	be	AUX
cet-3935	87	60	proposed	propose	VERB
cet-3935	87	61	.	.	PUNCT
cet-3935	88	1	the	the	DET
cet-3935	88	2	lr	lr	PROPN
cet-3935	88	3	image	image	NOUN
cet-3935	88	4	is	be	AUX
cet-3935	88	5	decomposed	decompose	VERB
cet-3935	88	6	into	into	ADP
cet-3935	88	7	low	low	ADJ
cet-3935	88	8	frequency	frequency	NOUN
cet-3935	88	9	and	and	CCONJ
cet-3935	88	10	high	high	ADJ
cet-3935	88	11	frequency	frequency	NOUN
cet-3935	88	12	subbands	subband	NOUN
cet-3935	88	13	using	use	VERB
cet-3935	88	14	wavelet	wavelet	NOUN
cet-3935	88	15	transform	transform	NOUN
cet-3935	88	16	firstly	firstly	ADV
cet-3935	88	17	,	,	PUNCT
cet-3935	88	18	then	then	ADV
cet-3935	88	19	the	the	DET
cet-3935	88	20	cs	cs	PROPN
cet-3935	88	21	algorithm	algorithm	NOUN
cet-3935	88	22	based	base	VERB
cet-3935	88	23	on	on	ADP
cet-3935	88	24	omp	omp	PROPN
cet-3935	88	25	for	for	ADP
cet-3935	88	26	the	the	DET
cet-3935	88	27	reconstruction	reconstruction	NOUN
cet-3935	88	28	of	of	ADP
cet-3935	88	29	two	two	NUM
cet-3935	88	30	bands	band	NOUN
cet-3935	88	31	.	.	PUNCT
cet-3935	89	1	finally	finally	ADV
cet-3935	89	2	get	get	VERB
cet-3935	89	3	the	the	DET
cet-3935	89	4	final	final	ADJ
cet-3935	89	5	reconstructed	reconstructed	ADJ
cet-3935	89	6	image	image	NOUN
cet-3935	89	7	by	by	ADP
cet-3935	89	8	wavelet	wavelet	NOUN
cet-3935	89	9	inverse	inverse	NOUN
cet-3935	89	10	transform	transform	NOUN
cet-3935	89	11	,	,	PUNCT
cet-3935	89	12	which	which	PRON
cet-3935	89	13	can	can	AUX
cet-3935	89	14	effectively	effectively	ADV
cet-3935	89	15	recover	recover	VERB
cet-3935	89	16	the	the	DET
cet-3935	89	17	high	high	ADJ
cet-3935	89	18	frequency	frequency	NOUN
cet-3935	89	19	information	information	NOUN
cet-3935	89	20	of	of	ADP
cet-3935	89	21	the	the	DET
cet-3935	89	22	image	image	NOUN
cet-3935	89	23	.	.	PUNCT
cet-3935	90	1	the	the	DET
cet-3935	90	2	experimental	experimental	ADJ
cet-3935	90	3	results	result	NOUN
cet-3935	90	4	show	show	VERB
cet-3935	90	5	that	that	SCONJ
cet-3935	90	6	the	the	DET
cet-3935	90	7	method	method	NOUN
cet-3935	90	8	combined	combine	VERB
cet-3935	90	9	with	with	ADP
cet-3935	90	10	the	the	DET
cet-3935	90	11	wavelet	wavelet	NOUN
cet-3935	90	12	multiresolution	multiresolution	NOUN
cet-3935	90	13	decomposition	decomposition	NOUN
cet-3935	90	14	and	and	CCONJ
cet-3935	90	15	the	the	DET
cet-3935	90	16	ability	ability	NOUN
cet-3935	90	17	of	of	ADP
cet-3935	90	18	cs	cs	PROPN
cet-3935	90	19	to	to	PART
cet-3935	90	20	recovery	recovery	VERB
cet-3935	90	21	the	the	DET
cet-3935	90	22	signal	signal	NOUN
cet-3935	90	23	in	in	ADP
cet-3935	90	24	smaller	small	ADJ
cet-3935	90	25	distortion	distortion	NOUN
cet-3935	90	26	ratio	ratio	NOUN
cet-3935	90	27	,	,	PUNCT
cet-3935	90	28	can	can	AUX
cet-3935	90	29	obtain	obtain	VERB
cet-3935	90	30	the	the	DET
cet-3935	90	31	ideal	ideal	ADJ
cet-3935	90	32	visual	visual	ADJ
cet-3935	90	33	effect	effect	NOUN
cet-3935	90	34	,	,	PUNCT
cet-3935	90	35	and	and	CCONJ
cet-3935	90	36	has	have	VERB
cet-3935	90	37	better	well	ADJ
cet-3935	90	38	reconstruction	reconstruction	NOUN
cet-3935	90	39	quality	quality	NOUN
cet-3935	90	40	from	from	ADP
cet-3935	90	41	the	the	DET
cet-3935	90	42	subjective	subjective	ADJ
cet-3935	90	43	and	and	CCONJ
cet-3935	90	44	objective	objective	ADJ
cet-3935	90	45	evaluation	evaluation	NOUN
cet-3935	90	46	index	index	NOUN
cet-3935	90	47	.	.	PUNCT
cet-3935	91	1	therefore	therefore	ADV
cet-3935	91	2	it	it	PRON
cet-3935	91	3	has	have	VERB
cet-3935	91	4	a	a	DET
cet-3935	91	5	broad	broad	ADJ
cet-3935	91	6	application	application	NOUN
cet-3935	91	7	prospect	prospect	NOUN
cet-3935	91	8	.	.	PUNCT
cet-3935	92	1	425	425	NUM
cet-3935	92	2	acknowledgments	acknowledgment	NOUN
cet-3935	92	3	this	this	DET
cet-3935	92	4	work	work	NOUN
cet-3935	92	5	was	be	AUX
cet-3935	92	6	supported	support	VERB
cet-3935	92	7	by	by	ADP
cet-3935	92	8	programs	program	NOUN
cet-3935	92	9	of	of	ADP
cet-3935	92	10	sichuan	sichuan	PROPN
cet-3935	92	11	provincial	provincial	PROPN
cet-3935	92	12	department	department	PROPN
cet-3935	92	13	of	of	ADP
cet-3935	92	14	education	education	PROPN
cet-3935	92	15	(	(	PUNCT
cet-3935	92	16	13zb0138	13zb0138	NUM
cet-3935	92	17	)	)	PUNCT
cet-3935	92	18	,	,	PUNCT
cet-3935	92	19	programs	program	NOUN
cet-3935	92	20	of	of	ADP
cet-3935	92	21	artificial	artificial	ADJ
cet-3935	92	22	intelligence	intelligence	NOUN
cet-3935	92	23	key	key	NOUN
cet-3935	92	24	laboratory	laboratory	NOUN
cet-3935	92	25	of	of	ADP
cet-3935	92	26	sichuan	sichuan	PROPN
cet-3935	92	27	province	province	PROPN
cet-3935	92	28	(	(	PUNCT
cet-3935	92	29	2013ryy02	2013ryy02	NOUN
cet-3935	92	30	)	)	PUNCT
cet-3935	92	31	and	and	CCONJ
cet-3935	92	32	programs	program	NOUN
cet-3935	92	33	of	of	ADP
cet-3935	92	34	sichuan	sichuan	PROPN
cet-3935	92	35	university	university	PROPN
cet-3935	92	36	of	of	ADP
cet-3935	92	37	science	science	PROPN
cet-3935	92	38	&	&	CCONJ
cet-3935	92	39	engineering	engineering	PROPN
cet-3935	92	40	teaching	teaching	NOUN
cet-3935	92	41	reform	reform	NOUN
cet-3935	92	42	(	(	PUNCT
cet-3935	92	43	jg-1415	jg-1415	NOUN
cet-3935	92	44	)	)	PUNCT
cet-3935	92	45	.	.	PUNCT
cet-3935	93	1	reference	reference	PROPN
cet-3935	93	2	becker	becker	PROPN
cet-3935	93	3	s.	s.	PROPN
cet-3935	93	4	,	,	PUNCT
cet-3935	93	5	bobin	bobin	PROPN
cet-3935	93	6	j.	j.	PROPN
cet-3935	93	7	,	,	PUNCT
cet-3935	93	8	candes	cande	VERB
cet-3935	93	9	e.	e.	PROPN
cet-3935	93	10	,	,	PUNCT
cet-3935	93	11	2009	2009	NUM
cet-3935	93	12	,	,	PUNCT
cet-3935	93	13	nesta	nesta	NOUN
cet-3935	93	14	:	:	PUNCT
cet-3935	93	15	a	a	DET
cet-3935	93	16	fast	fast	ADJ
cet-3935	93	17	and	and	CCONJ
cet-3935	93	18	accurate	accurate	ADJ
cet-3935	93	19	first	first	ADJ
cet-3935	93	20	-	-	PUNCT
cet-3935	93	21	order	order	NOUN
cet-3935	93	22	method	method	NOUN
cet-3935	93	23	for	for	ADP
cet-3935	93	24	sparse	sparse	ADJ
cet-3935	93	25	recovery	recovery	NOUN
cet-3935	93	26	,	,	PUNCT
cet-3935	93	27	siam	siam	ADJ
cet-3935	93	28	journal	journal	NOUN
cet-3935	93	29	on	on	ADP
cet-3935	93	30	imaging	imaging	NOUN
cet-3935	93	31	science	science	NOUN
cet-3935	93	32	,	,	PUNCT
cet-3935	93	33	4(1	4(1	NOUN
cet-3935	93	34	)	)	PUNCT
cet-3935	93	35	,	,	PUNCT
cet-3935	93	36	1	1	NUM
cet-3935	93	37	-	-	SYM
cet-3935	93	38	39	39	NUM
cet-3935	93	39	,	,	PUNCT
cet-3935	93	40	doi	doi	NOUN
cet-3935	93	41	:	:	PUNCT
cet-3935	93	42	10.1137/090756855	10.1137/090756855	NUM
cet-3935	93	43	candes	cande	NOUN
cet-3935	93	44	e.	e.	PROPN
cet-3935	93	45	,	,	PUNCT
cet-3935	93	46	2006	2006	NUM
cet-3935	93	47	,	,	PUNCT
cet-3935	93	48	compressive	compressive	ADJ
cet-3935	93	49	sampling	sampling	NOUN
cet-3935	93	50	,	,	PUNCT
cet-3935	93	51	proceedings	proceeding	NOUN
cet-3935	93	52	of	of	ADP
cet-3935	93	53	the	the	DET
cet-3935	93	54	international	international	ADJ
cet-3935	93	55	congress	congress	PROPN
cet-3935	93	56	of	of	ADP
cet-3935	93	57	mathematics	mathematics	PROPN
cet-3935	93	58	,	,	PUNCT
cet-3935	93	59	madrid	madrid	PROPN
cet-3935	93	60	:	:	PUNCT
cet-3935	93	61	european	european	PROPN
cet-3935	93	62	mathematical	mathematical	PROPN
cet-3935	93	63	society	society	PROPN
cet-3935	93	64	publishing	publishing	PROPN
cet-3935	93	65	house	house	NOUN
cet-3935	93	66	,	,	PUNCT
cet-3935	93	67	1433	1433	NUM
cet-3935	93	68	-	-	SYM
cet-3935	93	69	1452	1452	NUM
cet-3935	93	70	,	,	PUNCT
cet-3935	93	71	doi	doi	NOUN
cet-3935	93	72	:	:	PUNCT
cet-3935	93	73	10.4171/022	10.4171/022	NUM
cet-3935	93	74	-	-	SYM
cet-3935	93	75	3/69	3/69	NUM
cet-3935	93	76	donoho	donoho	NOUN
cet-3935	93	77	d.	d.	PROPN
cet-3935	93	78	,	,	PUNCT
cet-3935	93	79	2006	2006	NUM
cet-3935	93	80	,	,	PUNCT
cet-3935	93	81	compressed	compress	VERB
cet-3935	93	82	sensing	sensing	NOUN
cet-3935	93	83	,	,	PUNCT
cet-3935	93	84	ieee	ieee	NOUN
cet-3935	93	85	trans	tran	NOUN
cet-3935	93	86	on	on	ADP
cet-3935	93	87	information	information	NOUN
cet-3935	93	88	theory	theory	NOUN
cet-3935	93	89	,	,	PUNCT
cet-3935	93	90	52(4	52(4	NUM
cet-3935	93	91	)	)	PUNCT
cet-3935	93	92	,	,	PUNCT
cet-3935	93	93	1289	1289	NUM
cet-3935	93	94	-	-	SYM
cet-3935	93	95	1306	1306	NUM
cet-3935	93	96	,	,	PUNCT
cet-3935	93	97	doi	doi	NOUN
cet-3935	93	98	:	:	PUNCT
cet-3935	93	99	10.1109	10.1109	NUM
cet-3935	93	100	/	/	SYM
cet-3935	93	101	tit.2006.871582	tit.2006.871582	PROPN
cet-3935	93	102	fan	fan	PROPN
cet-3935	93	103	b.	b.	PROPN
cet-3935	93	104	,	,	PUNCT
cet-3935	93	105	yang	yang	PROPN
cet-3935	93	106	x.m	x.m	PROPN
cet-3935	93	107	.	.	PROPN
cet-3935	93	108	,	,	PUNCT
cet-3935	93	109	hu	hu	PROPN
cet-3935	94	1	x.s	x.s	PROPN
cet-3935	94	2	.	.	PROPN
cet-3935	94	3	,	,	PUNCT
cet-3935	94	4	2003	2003	NUM
cet-3935	94	5	,	,	PUNCT
cet-3935	94	6	super	super	ADJ
cet-3935	94	7	-	-	ADJ
cet-3935	94	8	resolution	resolution	ADJ
cet-3935	94	9	image	image	NOUN
cet-3935	94	10	reconstruction	reconstruction	NOUN
cet-3935	94	11	algorithms	algorithm	NOUN
cet-3935	94	12	based	base	VERB
cet-3935	94	13	on	on	ADP
cet-3935	94	14	compressive	compressive	ADJ
cet-3935	94	15	sensing	sensing	NOUN
cet-3935	94	16	,	,	PUNCT
cet-3935	94	17	journal	journal	NOUN
cet-3935	94	18	of	of	ADP
cet-3935	94	19	computer	computer	NOUN
cet-3935	94	20	applications	application	NOUN
cet-3935	94	21	,	,	PUNCT
cet-3935	94	22	33(2	33(2	NUM
cet-3935	94	23	)	)	PUNCT
cet-3935	94	24	,	,	PUNCT
cet-3935	94	25	480	480	NUM
cet-3935	94	26	-	-	SYM
cet-3935	94	27	483	483	NUM
cet-3935	94	28	goldstein	goldstein	PROPN
cet-3935	94	29	t.	t.	PROPN
cet-3935	94	30	,	,	PUNCT
cet-3935	94	31	osher	osher	PROPN
cet-3935	94	32	s.	s.	PROPN
cet-3935	94	33	,	,	PUNCT
cet-3935	94	34	2009	2009	NUM
cet-3935	94	35	,	,	PUNCT
cet-3935	94	36	the	the	DET
cet-3935	94	37	split	split	ADJ
cet-3935	94	38	bregman	bregman	NOUN
cet-3935	94	39	method	method	NOUN
cet-3935	94	40	for	for	ADP
cet-3935	94	41	l1	l1	PROPN
cet-3935	94	42	regularized	regularize	VERB
cet-3935	94	43	problems	problem	NOUN
cet-3935	94	44	,	,	PUNCT
cet-3935	94	45	siam	siam	ADJ
cet-3935	94	46	journal	journal	NOUN
cet-3935	94	47	on	on	ADP
cet-3935	94	48	image	image	NOUN
cet-3935	94	49	science	science	NOUN
cet-3935	94	50	,	,	PUNCT
cet-3935	94	51	2(2	2(2	NUM
cet-3935	94	52	)	)	PUNCT
cet-3935	94	53	,	,	PUNCT
cet-3935	94	54	323	323	NUM
cet-3935	94	55	-	-	SYM
cet-3935	94	56	343	343	NUM
cet-3935	94	57	,	,	PUNCT
cet-3935	94	58	doi	doi	NOUN
cet-3935	94	59	:	:	PUNCT
cet-3935	94	60	10.1137/080725891	10.1137/080725891	NUM
cet-3935	94	61	li	li	PROPN
cet-3935	94	62	x.x	x.x	PROPN
cet-3935	94	63	.	.	PROPN
cet-3935	94	64	,	,	PUNCT
cet-3935	95	1	wei	wei	PROPN
cet-3935	95	2	z.h	z.h	AUX
cet-3935	95	3	.	.	PROPN
cet-3935	95	4	,	,	PUNCT
cet-3935	95	5	2012	2012	NUM
cet-3935	95	6	,	,	PUNCT
cet-3935	95	7	compressed	compress	VERB
cet-3935	95	8	sensing	sense	VERB
cet-3935	95	9	video	video	NOUN
cet-3935	95	10	images	image	NOUN
cet-3935	95	11	recursive	recursive	ADJ
cet-3935	95	12	reconstruction	reconstruction	NOUN
cet-3935	95	13	algorithm	algorithm	NOUN
cet-3935	95	14	based	base	VERB
cet-3935	95	15	on	on	ADP
cet-3935	95	16	local	local	ADJ
cet-3935	95	17	autoregressive	autoregressive	ADJ
cet-3935	95	18	model	model	NOUN
cet-3935	95	19	,	,	PUNCT
cet-3935	95	20	acta	acta	PROPN
cet-3935	95	21	electronica	electronica	PROPN
cet-3935	95	22	sinica	sinica	PROPN
cet-3935	95	23	,	,	PUNCT
cet-3935	95	24	40(9	40(9	NUM
cet-3935	95	25	)	)	PUNCT
cet-3935	95	26	,	,	PUNCT
cet-3935	95	27	1795	1795	NUM
cet-3935	95	28	-	-	SYM
cet-3935	95	29	1800	1800	NUM
cet-3935	95	30	mallat	mallat	PROPN
cet-3935	95	31	s.	s.	PROPN
cet-3935	95	32	,	,	PUNCT
cet-3935	95	33	zhang	zhang	PROPN
cet-3935	95	34	z.	z.	PROPN
cet-3935	95	35	,	,	PUNCT
cet-3935	95	36	1993	1993	NUM
cet-3935	95	37	,	,	PUNCT
cet-3935	95	38	matching	match	VERB
cet-3935	95	39	pursuits	pursuit	NOUN
cet-3935	95	40	with	with	ADP
cet-3935	95	41	time	time	NOUN
cet-3935	95	42	frequency	frequency	NOUN
cet-3935	95	43	dictionaries	dictionary	NOUN
cet-3935	95	44	,	,	PUNCT
cet-3935	95	45	ieee	ieee	NOUN
cet-3935	95	46	transactions	transaction	NOUN
cet-3935	95	47	on	on	ADP
cet-3935	95	48	signal	signal	ADJ
cet-3935	95	49	process	process	NOUN
cet-3935	95	50	,	,	PUNCT
cet-3935	95	51	41(12	41(12	NUM
cet-3935	95	52	)	)	PUNCT
cet-3935	95	53	,	,	PUNCT
cet-3935	95	54	3397	3397	NUM
cet-3935	95	55	-	-	SYM
cet-3935	95	56	3415	3415	NUM
cet-3935	95	57	,	,	PUNCT
cet-3935	95	58	doi	doi	NOUN
cet-3935	95	59	:	:	PUNCT
cet-3935	95	60	10.1109/78.258082	10.1109/78.258082	PROPN
cet-3935	95	61	mun	mun	PROPN
cet-3935	95	62	s.	s.	PROPN
cet-3935	95	63	,	,	PUNCT
cet-3935	95	64	fowler	fowler	PROPN
cet-3935	95	65	j.e	j.e	PROPN
cet-3935	95	66	.	.	PROPN
cet-3935	95	67	,	,	PUNCT
cet-3935	95	68	2011	2011	NUM
cet-3935	95	69	,	,	PUNCT
cet-3935	95	70	residual	residual	ADJ
cet-3935	95	71	reconstruction	reconstruction	NOUN
cet-3935	95	72	for	for	ADP
cet-3935	95	73	block	block	NOUN
cet-3935	95	74	-	-	PUNCT
cet-3935	95	75	based	base	VERB
cet-3935	95	76	compressed	compressed	ADJ
cet-3935	95	77	sensing	sensing	NOUN
cet-3935	95	78	of	of	ADP
cet-3935	95	79	video	video	NOUN
cet-3935	95	80	,	,	PUNCT
cet-3935	95	81	proceedings	proceeding	NOUN
cet-3935	95	82	of	of	ADP
cet-3935	95	83	the	the	DET
cet-3935	95	84	data	data	NOUN
cet-3935	95	85	compression	compression	NOUN
cet-3935	95	86	conference	conference	NOUN
cet-3935	95	87	(	(	PUNCT
cet-3935	95	88	dcc	dcc	PROPN
cet-3935	95	89	)	)	PUNCT
cet-3935	95	90	,	,	PUNCT
cet-3935	95	91	snowbird	snowbird	NOUN
cet-3935	95	92	,	,	PUNCT
cet-3935	95	93	usa	usa	PROPN
cet-3935	95	94	:	:	PUNCT
cet-3935	95	95	ieee	ieee	PROPN
cet-3935	95	96	press	press	NOUN
cet-3935	95	97	,	,	PUNCT
cet-3935	95	98	183	183	NUM
cet-3935	95	99	-	-	SYM
cet-3935	95	100	192	192	NUM
cet-3935	95	101	,	,	PUNCT
cet-3935	95	102	doi	doi	NOUN
cet-3935	95	103	:	:	PUNCT
cet-3935	95	104	10.1109	10.1109	NUM
cet-3935	95	105	/	/	SYM
cet-3935	95	106	dcc.2011.25	dcc.2011.25	PROPN
cet-3935	95	107	pati	pati	PROPN
cet-3935	95	108	y.c	y.c	PROPN
cet-3935	95	109	.	.	PROPN
cet-3935	95	110	,	,	PUNCT
cet-3935	95	111	rezaiifar	rezaiifar	PROPN
cet-3935	95	112	r.	r.	PROPN
cet-3935	95	113	,	,	PUNCT
cet-3935	95	114	krishnaprasad	krishnaprasad	PROPN
cet-3935	95	115	e.s	e.s	PROPN
cet-3935	95	116	.	.	PROPN
cet-3935	95	117	,	,	PUNCT
cet-3935	95	118	1993	1993	NUM
cet-3935	95	119	,	,	PUNCT
cet-3935	95	120	orthogonal	orthogonal	ADJ
cet-3935	95	121	matching	matching	NOUN
cet-3935	95	122	pursuit	pursuit	NOUN
cet-3935	95	123	:	:	PUNCT
cet-3935	95	124	recursive	recursive	ADJ
cet-3935	95	125	function	function	NOUN
cet-3935	95	126	approximation	approximation	NOUN
cet-3935	95	127	with	with	ADP
cet-3935	95	128	application	application	NOUN
cet-3935	95	129	to	to	ADP
cet-3935	95	130	wavelet	wavelet	NOUN
cet-3935	95	131	decomposition	decomposition	NOUN
cet-3935	95	132	,	,	PUNCT
cet-3935	95	133	proceedings	proceeding	NOUN
cet-3935	95	134	of	of	ADP
cet-3935	95	135	1993	1993	NUM
cet-3935	95	136	conference	conference	NOUN
cet-3935	95	137	record	record	NOUN
cet-3935	95	138	of	of	ADP
cet-3935	95	139	the	the	DET
cet-3935	95	140	twenty	twenty	NUM
cet-3935	95	141	-	-	PUNCT
cet-3935	95	142	seventh	seventh	ADJ
cet-3935	95	143	asilomar	asilomar	NOUN
cet-3935	95	144	conference	conference	NOUN
cet-3935	95	145	on	on	ADP
cet-3935	95	146	signals	signal	NOUN
cet-3935	95	147	,	,	PUNCT
cet-3935	95	148	systems	system	NOUN
cet-3935	95	149	and	and	CCONJ
cet-3935	95	150	computers	computer	NOUN
cet-3935	95	151	.	.	PUNCT
cet-3935	96	1	pacific	pacific	PROPN
cet-3935	96	2	grove	grove	PROPN
cet-3935	96	3	,	,	PUNCT
cet-3935	96	4	1	1	NUM
cet-3935	96	5	-	-	SYM
cet-3935	96	6	3	3	NUM
cet-3935	96	7	nov	nov	NOUN
cet-3935	96	8	,	,	PUNCT
cet-3935	96	9	40	40	NUM
cet-3935	96	10	-	-	SYM
cet-3935	96	11	44	44	NUM
cet-3935	96	12	,	,	PUNCT
cet-3935	96	13	doi	doi	NOUN
cet-3935	96	14	:	:	PUNCT
cet-3935	96	15	10.1109	10.1109	NUM
cet-3935	96	16	/	/	SYM
cet-3935	96	17	acssc.1993.342465	acssc.1993.342465	NUM
cet-3935	96	18	sen	sen	PROPN
cet-3935	96	19	p.	p.	PROPN
cet-3935	96	20	,	,	PUNCT
cet-3935	96	21	darabi	darabi	PROPN
cet-3935	96	22	s.	s.	PROPN
cet-3935	96	23	,	,	PUNCT
cet-3935	96	24	2009	2009	NUM
cet-3935	96	25	,	,	PUNCT
cet-3935	96	26	compressive	compressive	ADJ
cet-3935	96	27	image	image	NOUN
cet-3935	96	28	super	super	NOUN
cet-3935	96	29	-	-	NOUN
cet-3935	96	30	resolution	resolution	NOUN
cet-3935	96	31	,	,	PUNCT
cet-3935	96	32	proceedings	proceeding	NOUN
cet-3935	96	33	of	of	ADP
cet-3935	96	34	2009	2009	NUM
cet-3935	96	35	conference	conference	NOUN
cet-3935	96	36	record	record	NOUN
cet-3935	96	37	of	of	ADP
cet-3935	96	38	the	the	DET
cet-3935	96	39	forty	forty	NUM
cet-3935	96	40	-	-	PUNCT
cet-3935	96	41	third	third	NOUN
cet-3935	96	42	asilomar	asilomar	NOUN
cet-3935	96	43	conference	conference	NOUN
cet-3935	96	44	on	on	ADP
cet-3935	96	45	signals	signal	NOUN
cet-3935	96	46	,	,	PUNCT
cet-3935	96	47	systems	system	NOUN
cet-3935	96	48	and	and	CCONJ
cet-3935	96	49	computers	computer	NOUN
cet-3935	96	50	,	,	PUNCT
cet-3935	96	51	piscataway	piscataway	NOUN
cet-3935	96	52	:	:	PUNCT
cet-3935	96	53	ieee	ieee	NOUN
cet-3935	96	54	,	,	PUNCT
cet-3935	96	55	1235	1235	NUM
cet-3935	96	56	-	-	SYM
cet-3935	96	57	1242	1242	NUM
cet-3935	96	58	,	,	PUNCT
cet-3935	96	59	doi	doi	NOUN
cet-3935	96	60	:	:	PUNCT
cet-3935	96	61	10.1109	10.1109	NUM
cet-3935	96	62	/	/	SYM
cet-3935	96	63	acssc.2009.5469968	acssc.2009.5469968	PROPN
cet-3935	96	64	tramel	tramel	PROPN
cet-3935	96	65	e.	e.	PROPN
cet-3935	96	66	,	,	PUNCT
cet-3935	96	67	fowler	fowler	PROPN
cet-3935	96	68	j.e	j.e	PROPN
cet-3935	96	69	.	.	PROPN
cet-3935	96	70	,	,	PUNCT
cet-3935	96	71	2011	2011	NUM
cet-3935	96	72	,	,	PUNCT
cet-3935	96	73	video	video	NOUN
cet-3935	96	74	compressed	compress	VERB
cet-3935	96	75	sensing	sensing	NOUN
cet-3935	96	76	with	with	ADP
cet-3935	96	77	multihypothesis	multihypothesis	NOUN
cet-3935	96	78	,	,	PUNCT
cet-3935	96	79	proceedings	proceeding	NOUN
cet-3935	96	80	of	of	ADP
cet-3935	96	81	the	the	DET
cet-3935	96	82	data	data	NOUN
cet-3935	96	83	compression	compression	NOUN
cet-3935	96	84	conference(dcc	conference(dcc	PROPN
cet-3935	96	85	)	)	PUNCT
cet-3935	96	86	,	,	PUNCT
cet-3935	96	87	snowbird	snowbird	NOUN
cet-3935	96	88	,	,	PUNCT
cet-3935	96	89	usa	usa	PROPN
cet-3935	96	90	:	:	PUNCT
cet-3935	96	91	ieee	ieee	PROPN
cet-3935	96	92	press	press	NOUN
cet-3935	96	93	,	,	PUNCT
cet-3935	96	94	193	193	NUM
cet-3935	96	95	-	-	SYM
cet-3935	96	96	202	202	NUM
cet-3935	96	97	,	,	PUNCT
cet-3935	96	98	doi	doi	NOUN
cet-3935	96	99	:	:	PUNCT
cet-3935	96	100	10.1109	10.1109	NUM
cet-3935	96	101	/	/	SYM
cet-3935	96	102	dcc.2011.26	dcc.2011.26	PROPN
cet-3935	96	103	tu	tu	PROPN
cet-3935	96	104	j.h	j.h	PROPN
cet-3935	96	105	.	.	PROPN
cet-3935	96	106	,	,	PUNCT
cet-3935	96	107	2014	2014	NUM
cet-3935	96	108	,	,	PUNCT
cet-3935	96	109	a	a	DET
cet-3935	96	110	novel	novel	ADJ
cet-3935	96	111	building	building	NOUN
cet-3935	96	112	boundary	boundary	ADJ
cet-3935	96	113	extraction	extraction	NOUN
cet-3935	96	114	method	method	NOUN
cet-3935	96	115	for	for	ADP
cet-3935	96	116	high	high	ADJ
cet-3935	96	117	-	-	PUNCT
cet-3935	96	118	resolution	resolution	NOUN
cet-3935	96	119	aerial	aerial	ADJ
cet-3935	96	120	image	image	NOUN
cet-3935	96	121	.	.	PUNCT
cet-3935	97	1	review	review	NOUN
cet-3935	97	2	of	of	ADP
cet-3935	97	3	computer	computer	NOUN
cet-3935	97	4	engineer	engineer	NOUN
cet-3935	97	5	studies	study	NOUN
cet-3935	97	6	,	,	PUNCT
cet-3935	97	7	1(2	1(2	NUM
cet-3935	97	8	)	)	PUNCT
cet-3935	97	9	,	,	PUNCT
cet-3935	97	10	19	19	NUM
cet-3935	97	11	-	-	SYM
cet-3935	97	12	21	21	NUM
cet-3935	97	13	,	,	PUNCT
cet-3935	97	14	doi	doi	NOUN
cet-3935	97	15	:	:	PUNCT
cet-3935	97	16	zhao	zhao	PROPN
cet-3935	97	17	w.j	w.j	PROPN
cet-3935	97	18	.	.	PROPN
cet-3935	97	19	,	,	PUNCT
cet-3935	97	20	2014	2014	NUM
cet-3935	97	21	,	,	PUNCT
cet-3935	97	22	image	image	NOUN
cet-3935	97	23	super	super	ADJ
cet-3935	97	24	-	-	ADJ
cet-3935	97	25	resolution	resolution	ADJ
cet-3935	97	26	reconstruction	reconstruction	NOUN
cet-3935	97	27	algorithm	algorithm	NOUN
cet-3935	97	28	based	base	VERB
cet-3935	97	29	on	on	ADP
cet-3935	97	30	compressive	compressive	ADJ
cet-3935	97	31	sensing	sensing	NOUN
cet-3935	97	32	,	,	PUNCT
cet-3935	97	33	jin	jin	PROPN
cet-3935	97	34	lin	lin	PROPN
cet-3935	97	35	university	university	PROPN
cet-3935	97	36	,	,	PUNCT
cet-3935	97	37	6	6	NUM
cet-3935	97	38	zuo	zuo	PROPN
cet-3935	97	39	y.l	y.l	PROPN
cet-3935	97	40	.	.	PROPN
cet-3935	97	41	,	,	PUNCT
cet-3935	97	42	ma	ma	PROPN
cet-3935	97	43	z.q	z.q	PROPN
cet-3935	97	44	.	.	PROPN
cet-3935	97	45	,	,	PUNCT
cet-3935	97	46	zuo	zuo	PROPN
cet-3935	97	47	x.y	x.y	PROPN
cet-3935	97	48	.	.	PROPN
cet-3935	97	49	,	,	PUNCT
cet-3935	97	50	2015	2015	NUM
cet-3935	97	51	,	,	PUNCT
cet-3935	97	52	super	super	ADJ
cet-3935	97	53	-	-	ADJ
cet-3935	97	54	resolution	resolution	ADJ
cet-3935	97	55	reconstruction	reconstruction	NOUN
cet-3935	97	56	method	method	NOUN
cet-3935	97	57	based	base	VERB
cet-3935	97	58	on	on	ADP
cet-3935	97	59	wavelet	wavelet	NOUN
cet-3935	97	60	domain	domain	NOUN
cet-3935	97	61	and	and	CCONJ
cet-3935	97	62	compressive	compressive	ADJ
cet-3935	97	63	sensing	sensing	NOUN
cet-3935	97	64	,	,	PUNCT
cet-3935	97	65	video	video	NOUN
cet-3935	97	66	engineering	engineering	NOUN
cet-3935	97	67	,	,	PUNCT
cet-3935	97	68	39(9	39(9	NUM
cet-3935	97	69	)	)	PUNCT
cet-3935	97	70	,	,	PUNCT
cet-3935	97	71	23	23	NUM
cet-3935	97	72	-	-	SYM
cet-3935	97	73	27	27	NUM
cet-3935	97	74	426	426	NUM
cet-3935	97	75	http://dx.doi.org/10.1137/090756855	http://dx.doi.org/10.1137/090756855	NOUN
cet-3935	97	76	http://dx.doi.org/10.1109/tit.2006.871582	http://dx.doi.org/10.1109/tit.2006.871582	NOUN
cet-3935	97	77	http://dx.doi.org/10.1137/080725891	http://dx.doi.org/10.1137/080725891	ADJ
cet-3935	97	78	http://dx.doi.org/10.1109/78.258082	http://dx.doi.org/10.1109/78.258082	PROPN
cet-3935	97	79	http://dx.doi.org/10.1109/dcc.2011.25	http://dx.doi.org/10.1109/dcc.2011.25	PROPN
cet-3935	97	80	http://dx.doi.org/10.1109/acssc.1993.342465	http://dx.doi.org/10.1109/acssc.1993.342465	NOUN
cet-3935	97	81	http://dx.doi.org/10.1109/acssc.2009.5469968	http://dx.doi.org/10.1109/acssc.2009.5469968	NOUN
cet-3935	97	82	http://dx.doi.org/10.1109/dcc.2011.26	http://dx.doi.org/10.1109/dcc.2011.26	VERB