id	sid	tid	token	lemma	pos
fcis-9761	1	1	frontiers	frontier	NOUN
fcis-9761	1	2	in	in	ADP
fcis-9761	1	3	computing	computing	NOUN
fcis-9761	1	4	and	and	CCONJ
fcis-9761	1	5	intelligent	intelligent	ADJ
fcis-9761	1	6	systems	system	NOUN
fcis-9761	1	7	issn	issn	VERB
fcis-9761	1	8	:	:	PUNCT
fcis-9761	1	9	2832	2832	NUM
fcis-9761	1	10	-	-	SYM
fcis-9761	1	11	6024	6024	NUM
fcis-9761	1	12	|	|	NOUN
fcis-9761	1	13	vol	vol	NOUN
fcis-9761	1	14	.	.	PROPN
fcis-9761	2	1	4	4	NUM
fcis-9761	2	2	,	,	PUNCT
fcis-9761	2	3	no	no	INTJ
fcis-9761	2	4	.	.	NOUN
fcis-9761	2	5	2	2	NUM
fcis-9761	2	6	,	,	PUNCT
fcis-9761	2	7	2023	2023	NUM
fcis-9761	2	8	27	27	NUM
fcis-9761	2	9	a	a	DET
fcis-9761	2	10	lightweight	lightweight	ADJ
fcis-9761	2	11	dual‐branch	dual‐branch	NOUN
fcis-9761	2	12	image	image	NOUN
fcis-9761	2	13	dehazing	dehazing	NOUN
fcis-9761	2	14	network	network	NOUN
fcis-9761	2	15	based	base	VERB
fcis-9761	2	16	on	on	ADP
fcis-9761	2	17	associative	associative	ADJ
fcis-9761	2	18	learning	learn	VERB
fcis-9761	2	19	xiaoxiao	xiaoxiao	PROPN
fcis-9761	2	20	xu	xu	PROPN
fcis-9761	3	1	*	*	PUNCT
fcis-9761	3	2	college	college	NOUN
fcis-9761	3	3	of	of	ADP
fcis-9761	3	4	computer	computer	NOUN
fcis-9761	3	5	science	science	NOUN
fcis-9761	3	6	and	and	CCONJ
fcis-9761	3	7	technology	technology	NOUN
fcis-9761	3	8	,	,	PUNCT
fcis-9761	3	9	qingdao	qingdao	PROPN
fcis-9761	3	10	university	university	PROPN
fcis-9761	3	11	,	,	PUNCT
fcis-9761	3	12	qingdao	qingdao	PROPN
fcis-9761	3	13	shandong	shandong	PROPN
fcis-9761	3	14	,	,	PUNCT
fcis-9761	3	15	266000	266000	NUM
fcis-9761	3	16	,	,	PUNCT
fcis-9761	3	17	china	china	PROPN
fcis-9761	3	18	*	*	PUNCT
fcis-9761	3	19	corresponding	correspond	VERB
fcis-9761	3	20	author	author	NOUN
fcis-9761	3	21	email	email	NOUN
fcis-9761	3	22	:	:	PUNCT
fcis-9761	3	23	xxx77904@163.com	xxx77904@163.com	X
fcis-9761	4	1	abstract	abstract	NOUN
fcis-9761	4	2	:	:	PUNCT
fcis-9761	4	3	haze	haze	NOUN
fcis-9761	4	4	degrades	degrade	VERB
fcis-9761	4	5	the	the	DET
fcis-9761	4	6	clarity	clarity	NOUN
fcis-9761	4	7	,	,	PUNCT
fcis-9761	4	8	contrast	contrast	NOUN
fcis-9761	4	9	,	,	PUNCT
fcis-9761	4	10	and	and	CCONJ
fcis-9761	4	11	details	detail	NOUN
fcis-9761	4	12	of	of	ADP
fcis-9761	4	13	images	image	NOUN
fcis-9761	4	14	,	,	PUNCT
fcis-9761	4	15	resulting	result	VERB
fcis-9761	4	16	in	in	ADP
fcis-9761	4	17	a	a	DET
fcis-9761	4	18	decrease	decrease	NOUN
fcis-9761	4	19	in	in	ADP
fcis-9761	4	20	image	image	NOUN
fcis-9761	4	21	quality	quality	NOUN
fcis-9761	4	22	.	.	PUNCT
fcis-9761	5	1	image	image	NOUN
fcis-9761	5	2	dehazing	dehazing	NOUN
fcis-9761	5	3	provides	provide	VERB
fcis-9761	5	4	a	a	DET
fcis-9761	5	5	means	mean	NOUN
fcis-9761	5	6	to	to	PART
fcis-9761	5	7	obtain	obtain	VERB
fcis-9761	5	8	clearer	clear	ADJ
fcis-9761	5	9	and	and	CCONJ
fcis-9761	5	10	more	more	ADV
fcis-9761	5	11	accurate	accurate	ADJ
fcis-9761	5	12	image	image	NOUN
fcis-9761	5	13	information	information	NOUN
fcis-9761	5	14	.	.	PUNCT
fcis-9761	6	1	traditional	traditional	ADJ
fcis-9761	6	2	methods	method	NOUN
fcis-9761	6	3	for	for	ADP
fcis-9761	6	4	haze	haze	NOUN
fcis-9761	6	5	removal	removal	NOUN
fcis-9761	6	6	typically	typically	ADV
fcis-9761	6	7	rely	rely	VERB
fcis-9761	6	8	on	on	ADP
fcis-9761	6	9	manually	manually	ADV
fcis-9761	6	10	designed	design	VERB
fcis-9761	6	11	features	feature	NOUN
fcis-9761	6	12	and	and	CCONJ
fcis-9761	6	13	models	model	NOUN
fcis-9761	6	14	,	,	PUNCT
fcis-9761	6	15	limiting	limit	VERB
fcis-9761	6	16	their	their	PRON
fcis-9761	6	17	performance	performance	NOUN
fcis-9761	6	18	in	in	ADP
fcis-9761	6	19	complex	complex	ADJ
fcis-9761	6	20	scenes	scene	NOUN
fcis-9761	6	21	.	.	PUNCT
fcis-9761	7	1	in	in	ADP
fcis-9761	7	2	recent	recent	ADJ
fcis-9761	7	3	years	year	NOUN
fcis-9761	7	4	,	,	PUNCT
fcis-9761	7	5	the	the	DET
fcis-9761	7	6	rapid	rapid	ADJ
fcis-9761	7	7	advancement	advancement	NOUN
fcis-9761	7	8	of	of	ADP
fcis-9761	7	9	deep	deep	ADJ
fcis-9761	7	10	learning	learning	NOUN
fcis-9761	7	11	has	have	AUX
fcis-9761	7	12	offered	offer	VERB
fcis-9761	7	13	new	new	ADJ
fcis-9761	7	14	insights	insight	NOUN
fcis-9761	7	15	into	into	ADP
fcis-9761	7	16	addressing	address	VERB
fcis-9761	7	17	the	the	DET
fcis-9761	7	18	image	image	NOUN
fcis-9761	7	19	dehazing	dehazing	NOUN
fcis-9761	7	20	problem	problem	NOUN
fcis-9761	7	21	.	.	PUNCT
fcis-9761	8	1	this	this	DET
fcis-9761	8	2	paper	paper	NOUN
fcis-9761	8	3	proposes	propose	VERB
fcis-9761	8	4	a	a	DET
fcis-9761	8	5	lightweight	lightweight	ADJ
fcis-9761	8	6	dualbranch	dualbranch	ADJ
fcis-9761	8	7	image	image	NOUN
fcis-9761	8	8	dehazing	dehaze	VERB
fcis-9761	8	9	network	network	NOUN
fcis-9761	8	10	based	base	VERB
fcis-9761	8	11	on	on	ADP
fcis-9761	8	12	associative	associative	ADJ
fcis-9761	8	13	learning	learning	NOUN
fcis-9761	8	14	(	(	PUNCT
fcis-9761	8	15	ldanet	ldanet	NOUN
fcis-9761	8	16	)	)	PUNCT
fcis-9761	8	17	.	.	PUNCT
fcis-9761	9	1	the	the	DET
fcis-9761	9	2	network	network	NOUN
fcis-9761	9	3	consists	consist	VERB
fcis-9761	9	4	of	of	ADP
fcis-9761	9	5	a	a	DET
fcis-9761	9	6	lightweight	lightweight	ADJ
fcis-9761	9	7	dehazing	dehazing	NOUN
fcis-9761	9	8	subnetwork	subnetwork	NOUN
fcis-9761	9	9	(	(	PUNCT
fcis-9761	9	10	ldsn	ldsn	NOUN
fcis-9761	9	11	)	)	PUNCT
fcis-9761	9	12	and	and	CCONJ
fcis-9761	9	13	a	a	DET
fcis-9761	9	14	lightweight	lightweight	ADJ
fcis-9761	9	15	image	image	NOUN
fcis-9761	9	16	enhancement	enhancement	NOUN
fcis-9761	9	17	subnetwork	subnetwork	NOUN
fcis-9761	9	18	(	(	PUNCT
fcis-9761	9	19	lesn	lesn	PROPN
fcis-9761	9	20	)	)	PUNCT
fcis-9761	9	21	.	.	PUNCT
fcis-9761	10	1	to	to	PART
fcis-9761	10	2	reduce	reduce	VERB
fcis-9761	10	3	computational	computational	ADJ
fcis-9761	10	4	and	and	CCONJ
fcis-9761	10	5	parameter	parameter	NOUN
fcis-9761	10	6	complexity	complexity	NOUN
fcis-9761	10	7	,	,	PUNCT
fcis-9761	10	8	the	the	DET
fcis-9761	10	9	tied	tie	VERB
fcis-9761	10	10	block	block	NOUN
fcis-9761	10	11	convolution	convolution	NOUN
fcis-9761	10	12	(	(	PUNCT
fcis-9761	10	13	tbc	tbc	NOUN
fcis-9761	10	14	)	)	PUNCT
fcis-9761	10	15	is	be	AUX
fcis-9761	10	16	employed	employ	VERB
fcis-9761	10	17	,	,	PUNCT
fcis-9761	10	18	allowing	allow	VERB
fcis-9761	10	19	for	for	ADP
fcis-9761	10	20	parameter	parameter	NOUN
fcis-9761	10	21	sharing	sharing	NOUN
fcis-9761	10	22	among	among	ADP
fcis-9761	10	23	components	component	NOUN
fcis-9761	10	24	.	.	PUNCT
fcis-9761	11	1	lastly	lastly	ADV
fcis-9761	11	2	,	,	PUNCT
fcis-9761	11	3	through	through	ADP
fcis-9761	11	4	associative	associative	ADJ
fcis-9761	11	5	learning	learning	NOUN
fcis-9761	11	6	,	,	PUNCT
fcis-9761	11	7	their	their	PRON
fcis-9761	11	8	distinctive	distinctive	ADJ
fcis-9761	11	9	features	feature	NOUN
fcis-9761	11	10	are	be	AUX
fcis-9761	11	11	mapped	map	VERB
fcis-9761	11	12	.	.	PUNCT
fcis-9761	12	1	extensive	extensive	ADJ
fcis-9761	12	2	experiments	experiment	NOUN
fcis-9761	12	3	on	on	ADP
fcis-9761	12	4	synthetic	synthetic	ADJ
fcis-9761	12	5	and	and	CCONJ
fcis-9761	12	6	real	real	ADJ
fcis-9761	12	7	-	-	PUNCT
fcis-9761	12	8	world	world	NOUN
fcis-9761	12	9	datasets	dataset	NOUN
fcis-9761	12	10	demonstrate	demonstrate	VERB
fcis-9761	12	11	the	the	DET
fcis-9761	12	12	superiority	superiority	NOUN
fcis-9761	12	13	of	of	ADP
fcis-9761	12	14	our	our	PRON
fcis-9761	12	15	approach	approach	NOUN
fcis-9761	12	16	in	in	ADP
fcis-9761	12	17	qualitative	qualitative	ADJ
fcis-9761	12	18	comparisons	comparison	NOUN
fcis-9761	12	19	and	and	CCONJ
fcis-9761	12	20	quantitative	quantitative	ADJ
fcis-9761	12	21	evaluations	evaluation	NOUN
fcis-9761	12	22	compared	compare	VERB
fcis-9761	12	23	to	to	ADP
fcis-9761	12	24	other	other	ADJ
fcis-9761	12	25	state	state	NOUN
fcis-9761	12	26	-	-	PUNCT
fcis-9761	12	27	of	of	ADP
fcis-9761	12	28	-	-	PUNCT
fcis-9761	12	29	the	the	DET
fcis-9761	12	30	-	-	PUNCT
fcis-9761	12	31	art	art	NOUN
fcis-9761	12	32	methods	method	NOUN
fcis-9761	12	33	.	.	PUNCT
fcis-9761	13	1	our	our	PRON
fcis-9761	13	2	method	method	NOUN
fcis-9761	13	3	holds	hold	VERB
fcis-9761	13	4	significant	significant	ADJ
fcis-9761	13	5	practical	practical	ADJ
fcis-9761	13	6	value	value	NOUN
fcis-9761	13	7	for	for	ADP
fcis-9761	13	8	real	real	ADJ
fcis-9761	13	9	-	-	PUNCT
fcis-9761	13	10	world	world	NOUN
fcis-9761	13	11	image	image	NOUN
fcis-9761	13	12	dehazing	dehaze	VERB
fcis-9761	13	13	scenarios	scenario	NOUN
fcis-9761	13	14	.	.	PUNCT
fcis-9761	14	1	keywords	keyword	NOUN
fcis-9761	14	2	:	:	PUNCT
fcis-9761	14	3	associative	associative	ADJ
fcis-9761	14	4	learning	learning	NOUN
fcis-9761	14	5	;	;	PUNCT
fcis-9761	14	6	encoder	encoder	NOUN
fcis-9761	14	7	-	-	PUNCT
fcis-9761	14	8	decoder	decoder	NOUN
fcis-9761	14	9	;	;	PUNCT
fcis-9761	14	10	image	image	NOUN
fcis-9761	14	11	dehazing	dehazing	NOUN
fcis-9761	14	12	;	;	PUNCT
fcis-9761	14	13	lightweight	lightweight	ADJ
fcis-9761	14	14	.	.	PUNCT
fcis-9761	15	1	1	1	X
fcis-9761	15	2	.	.	X
fcis-9761	15	3	introduction	introduction	NOUN
fcis-9761	15	4	in	in	ADP
fcis-9761	15	5	domains	domain	NOUN
fcis-9761	15	6	such	such	ADJ
fcis-9761	15	7	as	as	ADP
fcis-9761	15	8	transportation	transportation	NOUN
fcis-9761	15	9	,	,	PUNCT
fcis-9761	15	10	aerospace	aerospace	NOUN
fcis-9761	15	11	,	,	PUNCT
fcis-9761	15	12	and	and	CCONJ
fcis-9761	15	13	road	road	NOUN
fcis-9761	15	14	monitoring	monitoring	NOUN
fcis-9761	15	15	,	,	PUNCT
fcis-9761	15	16	haze	haze	VERB
fcis-9761	15	17	significantly	significantly	ADV
fcis-9761	15	18	reduces	reduce	VERB
fcis-9761	15	19	visibility	visibility	NOUN
fcis-9761	15	20	,	,	PUNCT
fcis-9761	15	21	affecting	affect	VERB
fcis-9761	15	22	various	various	ADJ
fcis-9761	15	23	aspects	aspect	NOUN
fcis-9761	15	24	of	of	ADP
fcis-9761	15	25	real	real	ADJ
fcis-9761	15	26	-	-	PUNCT
fcis-9761	15	27	life	life	NOUN
fcis-9761	15	28	scenarios	scenario	NOUN
fcis-9761	15	29	.	.	PUNCT
fcis-9761	16	1	therefore	therefore	ADV
fcis-9761	16	2	,	,	PUNCT
fcis-9761	16	3	dehazing	dehaze	VERB
fcis-9761	16	4	is	be	AUX
fcis-9761	16	5	a	a	DET
fcis-9761	16	6	crucial	crucial	ADJ
fcis-9761	16	7	task	task	NOUN
fcis-9761	16	8	aimed	aim	VERB
fcis-9761	16	9	at	at	ADP
fcis-9761	16	10	mitigating	mitigate	VERB
fcis-9761	16	11	the	the	DET
fcis-9761	16	12	impact	impact	NOUN
fcis-9761	16	13	of	of	ADP
fcis-9761	16	14	haze	haze	NOUN
fcis-9761	16	15	on	on	ADP
fcis-9761	16	16	different	different	ADJ
fcis-9761	16	17	systems	system	NOUN
fcis-9761	16	18	and	and	CCONJ
fcis-9761	16	19	enhancing	enhance	VERB
fcis-9761	16	20	their	their	PRON
fcis-9761	16	21	usability	usability	NOUN
fcis-9761	16	22	.	.	PUNCT
fcis-9761	17	1	the	the	DET
fcis-9761	17	2	atmospheric	atmospheric	ADJ
fcis-9761	17	3	scattering	scattering	NOUN
fcis-9761	17	4	model	model	NOUN
fcis-9761	17	5	(	(	PUNCT
fcis-9761	17	6	asm	asm	NOUN
fcis-9761	17	7	)	)	PUNCT
fcis-9761	18	1	[	[	X
fcis-9761	18	2	1	1	X
fcis-9761	18	3	]	]	PUNCT
fcis-9761	18	4	is	be	AUX
fcis-9761	18	5	a	a	DET
fcis-9761	18	6	mathematical	mathematical	ADJ
fcis-9761	18	7	model	model	NOUN
fcis-9761	18	8	that	that	PRON
fcis-9761	18	9	describes	describe	VERB
fcis-9761	18	10	the	the	DET
fcis-9761	18	11	scattering	scattering	NOUN
fcis-9761	18	12	and	and	CCONJ
fcis-9761	18	13	absorption	absorption	NOUN
fcis-9761	18	14	of	of	ADP
fcis-9761	18	15	light	light	NOUN
fcis-9761	18	16	during	during	ADP
fcis-9761	18	17	its	its	PRON
fcis-9761	18	18	propagation	propagation	NOUN
fcis-9761	18	19	through	through	ADP
fcis-9761	18	20	the	the	DET
fcis-9761	18	21	atmosphere	atmosphere	NOUN
fcis-9761	18	22	.	.	PUNCT
fcis-9761	19	1	it	it	PRON
fcis-9761	19	2	is	be	AUX
fcis-9761	19	3	employed	employ	VERB
fcis-9761	19	4	to	to	PART
fcis-9761	19	5	explain	explain	VERB
fcis-9761	19	6	the	the	DET
fcis-9761	19	7	process	process	NOUN
fcis-9761	19	8	of	of	ADP
fcis-9761	19	9	light	light	ADJ
fcis-9761	19	10	propagation	propagation	NOUN
fcis-9761	19	11	in	in	ADP
fcis-9761	19	12	the	the	DET
fcis-9761	19	13	atmosphere	atmosphere	NOUN
fcis-9761	19	14	,	,	PUNCT
fcis-9761	19	15	particularly	particularly	ADV
fcis-9761	19	16	under	under	ADP
fcis-9761	19	17	conditions	condition	NOUN
fcis-9761	19	18	of	of	ADP
fcis-9761	19	19	haze	haze	NOUN
fcis-9761	19	20	,	,	PUNCT
fcis-9761	19	21	atmospheric	atmospheric	ADJ
fcis-9761	19	22	pollution	pollution	NOUN
fcis-9761	19	23	,	,	PUNCT
fcis-9761	19	24	or	or	CCONJ
fcis-9761	19	25	long	long	ADJ
fcis-9761	19	26	-	-	PUNCT
fcis-9761	19	27	distance	distance	NOUN
fcis-9761	19	28	observations	observation	NOUN
fcis-9761	19	29	.	.	PUNCT
fcis-9761	20	1	the	the	DET
fcis-9761	20	2	asm	asm	NOUN
fcis-9761	20	3	can	can	AUX
fcis-9761	20	4	be	be	AUX
fcis-9761	20	5	formally	formally	ADV
fcis-9761	20	6	expressed	express	VERB
fcis-9761	20	7	as	as	SCONJ
fcis-9761	20	8	follows	follow	VERB
fcis-9761	20	9	:	:	PUNCT
fcis-9761	20	10	i(x	i(x	NOUN
fcis-9761	20	11	)	)	PUNCT
fcis-9761	21	1	=	=	PUNCT
fcis-9761	21	2	j(x)t(x)+a(1	j(x)t(x)+a(1	PROPN
fcis-9761	21	3	-	-	PUNCT
fcis-9761	21	4	t(x	t(x	PROPN
fcis-9761	21	5	)	)	PUNCT
fcis-9761	21	6	)	)	PUNCT
fcis-9761	22	1	(	(	PUNCT
fcis-9761	22	2	1	1	X
fcis-9761	22	3	)	)	PUNCT
fcis-9761	22	4	where	where	SCONJ
fcis-9761	22	5	i	i	PRON
fcis-9761	22	6	and	and	CCONJ
fcis-9761	22	7	j	j	PROPN
fcis-9761	22	8	represent	represent	VERB
fcis-9761	22	9	the	the	DET
fcis-9761	22	10	observed	observe	VERB
fcis-9761	22	11	hazy	hazy	ADJ
fcis-9761	22	12	and	and	CCONJ
fcis-9761	22	13	haze	haze	NOUN
fcis-9761	22	14	-	-	PUNCT
fcis-9761	22	15	free	free	ADJ
fcis-9761	22	16	images	image	NOUN
fcis-9761	22	17	,	,	PUNCT
fcis-9761	22	18	respectively	respectively	ADV
fcis-9761	22	19	,	,	PUNCT
fcis-9761	22	20	t	t	PROPN
fcis-9761	22	21	x	x	X
fcis-9761	22	22	e	e	NOUN
fcis-9761	22	23	denotes	denote	VERB
fcis-9761	22	24	the	the	DET
fcis-9761	22	25	medium	medium	ADJ
fcis-9761	22	26	transmission	transmission	NOUN
fcis-9761	22	27	map	map	NOUN
fcis-9761	22	28	,	,	PUNCT
fcis-9761	22	29	β	β	PROPN
fcis-9761	22	30	and	and	CCONJ
fcis-9761	22	31	d	d	NOUN
fcis-9761	22	32	x	x	PRON
fcis-9761	22	33	represent	represent	VERB
fcis-9761	22	34	the	the	DET
fcis-9761	22	35	atmospheric	atmospheric	ADJ
fcis-9761	22	36	scattering	scatter	VERB
fcis-9761	22	37	parameters	parameter	NOUN
fcis-9761	22	38	and	and	CCONJ
fcis-9761	22	39	scene	scene	NOUN
fcis-9761	22	40	depth	depth	NOUN
fcis-9761	22	41	,	,	PUNCT
fcis-9761	22	42	respectively	respectively	ADV
fcis-9761	22	43	,	,	PUNCT
fcis-9761	22	44	while	while	SCONJ
fcis-9761	22	45	x	x	PRON
fcis-9761	22	46	denotes	denote	VERB
fcis-9761	22	47	the	the	DET
fcis-9761	22	48	pixel	pixel	PROPN
fcis-9761	22	49	position	position	NOUN
fcis-9761	22	50	.	.	PUNCT
fcis-9761	23	1	based	base	VERB
fcis-9761	23	2	on	on	ADP
fcis-9761	23	3	different	different	ADJ
fcis-9761	23	4	principles	principle	NOUN
fcis-9761	23	5	,	,	PUNCT
fcis-9761	23	6	current	current	ADJ
fcis-9761	23	7	image	image	NOUN
fcis-9761	23	8	dehazing	dehazing	NOUN
fcis-9761	23	9	algorithms	algorithm	NOUN
fcis-9761	23	10	can	can	AUX
fcis-9761	23	11	be	be	AUX
fcis-9761	23	12	categorized	categorize	VERB
fcis-9761	23	13	into	into	ADP
fcis-9761	23	14	two	two	NUM
fcis-9761	23	15	main	main	ADJ
fcis-9761	23	16	types	type	NOUN
fcis-9761	23	17	:	:	PUNCT
fcis-9761	23	18	image	image	NOUN
fcis-9761	23	19	enhancement	enhancement	NOUN
fcis-9761	23	20	-	-	PUNCT
fcis-9761	23	21	based	base	VERB
fcis-9761	23	22	and	and	CCONJ
fcis-9761	23	23	image	image	NOUN
fcis-9761	23	24	restoration	restoration	NOUN
fcis-9761	23	25	-	-	PUNCT
fcis-9761	23	26	based	base	VERB
fcis-9761	23	27	dehazing	dehazing	NOUN
fcis-9761	23	28	algorithms	algorithm	NOUN
fcis-9761	23	29	.	.	PUNCT
fcis-9761	24	1	the	the	DET
fcis-9761	24	2	remaining	remain	VERB
fcis-9761	24	3	sections	section	NOUN
fcis-9761	24	4	of	of	ADP
fcis-9761	24	5	this	this	DET
fcis-9761	24	6	paper	paper	NOUN
fcis-9761	24	7	are	be	AUX
fcis-9761	24	8	structured	structure	VERB
fcis-9761	24	9	as	as	SCONJ
fcis-9761	24	10	follows	follow	VERB
fcis-9761	24	11	.	.	PUNCT
fcis-9761	25	1	in	in	ADP
fcis-9761	25	2	section	section	NOUN
fcis-9761	25	3	2	2	NUM
fcis-9761	25	4	,	,	PUNCT
fcis-9761	25	5	we	we	PRON
fcis-9761	25	6	provide	provide	VERB
fcis-9761	25	7	an	an	DET
fcis-9761	25	8	exposition	exposition	NOUN
fcis-9761	25	9	on	on	ADP
fcis-9761	25	10	the	the	DET
fcis-9761	25	11	research	research	NOUN
fcis-9761	25	12	status	status	NOUN
fcis-9761	25	13	of	of	ADP
fcis-9761	25	14	image	image	NOUN
fcis-9761	25	15	dehazing	dehazing	NOUN
fcis-9761	25	16	.	.	PUNCT
fcis-9761	26	1	in	in	ADP
fcis-9761	26	2	section	section	NOUN
fcis-9761	26	3	3	3	NUM
fcis-9761	26	4	,	,	PUNCT
fcis-9761	26	5	the	the	DET
fcis-9761	26	6	proposed	propose	VERB
fcis-9761	26	7	network	network	NOUN
fcis-9761	26	8	is	be	AUX
fcis-9761	26	9	presented	present	VERB
fcis-9761	26	10	in	in	ADP
fcis-9761	26	11	detail	detail	NOUN
fcis-9761	26	12	.	.	PUNCT
fcis-9761	27	1	in	in	ADP
fcis-9761	27	2	section	section	NOUN
fcis-9761	27	3	4	4	NUM
fcis-9761	27	4	,	,	PUNCT
fcis-9761	27	5	we	we	PRON
fcis-9761	27	6	objectively	objectively	ADV
fcis-9761	27	7	analyze	analyze	VERB
fcis-9761	27	8	the	the	DET
fcis-9761	27	9	experimental	experimental	ADJ
fcis-9761	27	10	results	result	NOUN
fcis-9761	27	11	,	,	PUNCT
fcis-9761	27	12	including	include	VERB
fcis-9761	27	13	evaluation	evaluation	NOUN
fcis-9761	27	14	metrics	metric	NOUN
fcis-9761	27	15	and	and	CCONJ
fcis-9761	27	16	comparative	comparative	ADJ
fcis-9761	27	17	images	image	NOUN
fcis-9761	27	18	.	.	PUNCT
fcis-9761	28	1	in	in	ADP
fcis-9761	28	2	section	section	NOUN
fcis-9761	28	3	5	5	NUM
fcis-9761	28	4	,	,	PUNCT
fcis-9761	28	5	we	we	PRON
fcis-9761	28	6	summarize	summarize	VERB
fcis-9761	28	7	this	this	DET
fcis-9761	28	8	paper	paper	NOUN
fcis-9761	28	9	.	.	PUNCT
fcis-9761	29	1	2	2	X
fcis-9761	29	2	.	.	X
fcis-9761	29	3	related	relate	VERB
fcis-9761	29	4	works	work	NOUN
fcis-9761	29	5	2.1	2.1	NUM
fcis-9761	29	6	.	.	PUNCT
fcis-9761	30	1	image	image	NOUN
fcis-9761	30	2	enhancement	enhancement	NOUN
fcis-9761	30	3	-	-	PUNCT
fcis-9761	30	4	based	base	VERB
fcis-9761	30	5	dehazing	dehazing	NOUN
fcis-9761	30	6	algorithms	algorithm	NOUN
fcis-9761	30	7	by	by	ADP
fcis-9761	30	8	adjusting	adjust	VERB
fcis-9761	30	9	the	the	DET
fcis-9761	30	10	grayscale	grayscale	NOUN
fcis-9761	30	11	levels	level	NOUN
fcis-9761	30	12	,	,	PUNCT
fcis-9761	30	13	the	the	DET
fcis-9761	30	14	contrast	contrast	NOUN
fcis-9761	30	15	of	of	ADP
fcis-9761	30	16	an	an	DET
fcis-9761	30	17	image	image	NOUN
fcis-9761	30	18	can	can	AUX
fcis-9761	30	19	be	be	AUX
fcis-9761	30	20	enhanced	enhance	VERB
fcis-9761	30	21	,	,	PUNCT
fcis-9761	30	22	thus	thus	ADV
fcis-9761	30	23	improving	improve	VERB
fcis-9761	30	24	its	its	PRON
fcis-9761	30	25	visual	visual	ADJ
fcis-9761	30	26	effect	effect	NOUN
fcis-9761	30	27	.	.	PUNCT
fcis-9761	31	1	histogram	histogram	NOUN
fcis-9761	31	2	equalization	equalization	NOUN
fcis-9761	31	3	algorithms	algorithm	NOUN
fcis-9761	31	4	are	be	AUX
fcis-9761	31	5	widely	widely	ADV
fcis-9761	31	6	used	use	VERB
fcis-9761	31	7	in	in	ADP
fcis-9761	31	8	digital	digital	ADJ
fcis-9761	31	9	image	image	NOUN
fcis-9761	31	10	processing	processing	NOUN
fcis-9761	31	11	,	,	PUNCT
fcis-9761	31	12	including	include	VERB
fcis-9761	31	13	both	both	CCONJ
fcis-9761	31	14	global	global	ADJ
fcis-9761	31	15	and	and	CCONJ
fcis-9761	31	16	local	local	ADJ
fcis-9761	31	17	histogram	histogram	NOUN
fcis-9761	31	18	equalization	equalization	NOUN
fcis-9761	31	19	methods	method	NOUN
fcis-9761	31	20	[	[	X
fcis-9761	31	21	2	2	NUM
fcis-9761	31	22	]	]	PUNCT
fcis-9761	31	23	.	.	PUNCT
fcis-9761	32	1	stark	stark	ADJ
fcis-9761	33	1	[	[	X
fcis-9761	33	2	2	2	NUM
fcis-9761	33	3	]	]	PUNCT
fcis-9761	33	4	and	and	CCONJ
fcis-9761	33	5	kim	kim	PROPN
fcis-9761	33	6	et	et	PROPN
fcis-9761	33	7	al	al	PROPN
fcis-9761	33	8	.	.	PUNCT
fcis-9761	34	1	[	[	X
fcis-9761	34	2	4	4	X
fcis-9761	34	3	]	]	PUNCT
fcis-9761	34	4	proposed	propose	VERB
fcis-9761	34	5	adaptive	adaptive	ADJ
fcis-9761	34	6	histogram	histogram	NOUN
fcis-9761	34	7	equalization	equalization	NOUN
fcis-9761	34	8	algorithms	algorithm	NOUN
fcis-9761	34	9	and	and	CCONJ
fcis-9761	34	10	partially	partially	ADV
fcis-9761	34	11	overlapping	overlap	VERB
fcis-9761	34	12	sub	sub	ADJ
fcis-9761	34	13	-	-	ADJ
fcis-9761	34	14	block	block	ADJ
fcis-9761	34	15	histogram	histogram	NOUN
fcis-9761	34	16	equalization	equalization	NOUN
fcis-9761	34	17	algorithms	algorithm	NOUN
fcis-9761	34	18	,	,	PUNCT
fcis-9761	34	19	respectively	respectively	ADV
fcis-9761	34	20	.	.	PUNCT
fcis-9761	35	1	russo	russo	PROPN
fcis-9761	36	1	[	[	X
fcis-9761	36	2	5	5	NUM
fcis-9761	36	3	]	]	PUNCT
fcis-9761	36	4	performed	perform	VERB
fcis-9761	36	5	equalization	equalization	NOUN
fcis-9761	36	6	on	on	ADP
fcis-9761	36	7	degraded	degraded	ADJ
fcis-9761	36	8	images	image	NOUN
fcis-9761	36	9	at	at	ADP
fcis-9761	36	10	multiple	multiple	ADJ
fcis-9761	36	11	scales	scale	NOUN
fcis-9761	36	12	.	.	PUNCT
fcis-9761	37	1	dippel	dippel	PROPN
fcis-9761	37	2	et	et	PROPN
fcis-9761	37	3	al	al	PROPN
fcis-9761	37	4	.	.	PUNCT
fcis-9761	38	1	[	[	X
fcis-9761	38	2	6	6	NUM
fcis-9761	38	3	]	]	PUNCT
fcis-9761	38	4	compared	compare	VERB
fcis-9761	38	5	two	two	NUM
fcis-9761	38	6	multi	multi	ADJ
fcis-9761	38	7	-	-	ADJ
fcis-9761	38	8	resolution	resolution	NOUN
fcis-9761	38	9	analysis	analysis	NOUN
fcis-9761	38	10	methods	method	NOUN
fcis-9761	38	11	,	,	PUNCT
fcis-9761	38	12	laplacian	laplacian	ADJ
fcis-9761	38	13	pyramid	pyramid	NOUN
fcis-9761	38	14	and	and	CCONJ
fcis-9761	38	15	wavelet	wavelet	NOUN
fcis-9761	38	16	transform	transform	NOUN
fcis-9761	38	17	,	,	PUNCT
fcis-9761	38	18	which	which	PRON
fcis-9761	38	19	exhibit	exhibit	VERB
fcis-9761	38	20	good	good	ADJ
fcis-9761	38	21	local	local	ADJ
fcis-9761	38	22	characteristics	characteristic	NOUN
fcis-9761	38	23	.	.	PUNCT
fcis-9761	39	1	the	the	DET
fcis-9761	39	2	retinex	retinex	ADJ
fcis-9761	39	3	model	model	NOUN
fcis-9761	39	4	[	[	X
fcis-9761	39	5	7	7	NUM
fcis-9761	39	6	]	]	PUNCT
fcis-9761	39	7	,	,	PUNCT
fcis-9761	39	8	based	base	VERB
fcis-9761	39	9	on	on	ADP
fcis-9761	39	10	the	the	DET
fcis-9761	39	11	theory	theory	NOUN
fcis-9761	39	12	of	of	ADP
fcis-9761	39	13	color	color	NOUN
fcis-9761	39	14	constancy	constancy	NOUN
fcis-9761	39	15	,	,	PUNCT
fcis-9761	39	16	includes	include	VERB
fcis-9761	39	17	both	both	DET
fcis-9761	39	18	single	single	ADJ
fcis-9761	39	19	-	-	PUNCT
fcis-9761	39	20	scale	scale	NOUN
fcis-9761	39	21	and	and	CCONJ
fcis-9761	39	22	multi	multi	ADJ
fcis-9761	39	23	-	-	ADJ
fcis-9761	39	24	scale	scale	ADJ
fcis-9761	39	25	retinex	retinex	ADJ
fcis-9761	39	26	algorithms	algorithm	NOUN
fcis-9761	39	27	.	.	PUNCT
fcis-9761	40	1	however	however	ADV
fcis-9761	40	2	,	,	PUNCT
fcis-9761	40	3	these	these	DET
fcis-9761	40	4	methods	method	NOUN
fcis-9761	40	5	overlook	overlook	VERB
fcis-9761	40	6	the	the	DET
fcis-9761	40	7	fundamental	fundamental	ADJ
fcis-9761	40	8	cause	cause	NOUN
fcis-9761	40	9	of	of	ADP
fcis-9761	40	10	image	image	NOUN
fcis-9761	40	11	blur	blur	NOUN
fcis-9761	40	12	,	,	PUNCT
fcis-9761	40	13	leading	lead	VERB
fcis-9761	40	14	to	to	ADP
fcis-9761	40	15	subpar	subpar	ADJ
fcis-9761	40	16	results	result	NOUN
fcis-9761	40	17	.	.	PUNCT
fcis-9761	41	1	2.2	2.2	NUM
fcis-9761	41	2	.	.	PUNCT
fcis-9761	41	3	image	image	NOUN
fcis-9761	41	4	restoration	restoration	NOUN
fcis-9761	41	5	-	-	PUNCT
fcis-9761	41	6	based	base	VERB
fcis-9761	41	7	dehazing	dehazing	NOUN
fcis-9761	41	8	algorithms	algorithm	NOUN
fcis-9761	41	9	these	these	DET
fcis-9761	41	10	methods	method	NOUN
fcis-9761	41	11	mainly	mainly	ADV
fcis-9761	41	12	include	include	VERB
fcis-9761	41	13	those	those	PRON
fcis-9761	41	14	based	base	VERB
fcis-9761	41	15	on	on	ADP
fcis-9761	41	16	prior	prior	ADJ
fcis-9761	41	17	knowledge	knowledge	NOUN
fcis-9761	41	18	and	and	CCONJ
fcis-9761	41	19	those	those	PRON
fcis-9761	41	20	based	base	VERB
fcis-9761	41	21	on	on	ADP
fcis-9761	41	22	learning	learn	VERB
fcis-9761	41	23	.	.	PUNCT
fcis-9761	42	1	he	he	PRON
fcis-9761	42	2	et	et	PROPN
fcis-9761	42	3	al	al	PROPN
fcis-9761	42	4	.	.	PUNCT
fcis-9761	43	1	[	[	X
fcis-9761	43	2	8	8	NUM
fcis-9761	43	3	]	]	PUNCT
fcis-9761	43	4	proposed	propose	VERB
fcis-9761	43	5	the	the	DET
fcis-9761	43	6	dark	dark	ADJ
fcis-9761	43	7	channel	channel	NOUN
fcis-9761	43	8	prior	prior	ADV
fcis-9761	43	9	(	(	PUNCT
fcis-9761	43	10	dcp	dcp	NOUN
fcis-9761	43	11	)	)	PUNCT
fcis-9761	43	12	dehazing	dehazing	NOUN
fcis-9761	43	13	algorithm	algorithm	NOUN
fcis-9761	43	14	,	,	PUNCT
fcis-9761	43	15	which	which	PRON
fcis-9761	43	16	utilizes	utilize	VERB
fcis-9761	43	17	the	the	DET
fcis-9761	43	18	atmospheric	atmospheric	ADJ
fcis-9761	43	19	scattering	scattering	NOUN
fcis-9761	43	20	model	model	NOUN
fcis-9761	43	21	(	(	PUNCT
fcis-9761	43	22	asm	asm	NOUN
fcis-9761	43	23	)	)	PUNCT
fcis-9761	43	24	for	for	ADP
fcis-9761	43	25	uniform	uniform	ADJ
fcis-9761	43	26	dehazing	dehazing	NOUN
fcis-9761	43	27	.	.	PUNCT
fcis-9761	44	1	tan	tan	PROPN
fcis-9761	45	1	[	[	X
fcis-9761	45	2	9	9	NUM
fcis-9761	45	3	]	]	PUNCT
fcis-9761	45	4	constructed	construct	VERB
fcis-9761	45	5	a	a	DET
fcis-9761	45	6	markov	markov	NOUN
fcis-9761	45	7	random	random	ADJ
fcis-9761	45	8	field	field	NOUN
fcis-9761	45	9	model	model	NOUN
fcis-9761	45	10	to	to	PART
fcis-9761	45	11	estimate	estimate	VERB
fcis-9761	45	12	the	the	DET
fcis-9761	45	13	cost	cost	NOUN
fcis-9761	45	14	function	function	NOUN
fcis-9761	45	15	of	of	ADP
fcis-9761	45	16	edge	edge	NOUN
fcis-9761	45	17	intensity	intensity	NOUN
fcis-9761	45	18	,	,	PUNCT
fcis-9761	45	19	resulting	result	VERB
fcis-9761	45	20	in	in	ADP
fcis-9761	45	21	significant	significant	ADJ
fcis-9761	45	22	improvement	improvement	NOUN
fcis-9761	45	23	in	in	ADP
fcis-9761	45	24	image	image	NOUN
fcis-9761	45	25	details	detail	NOUN
fcis-9761	45	26	.	.	PUNCT
fcis-9761	46	1	cai	cai	PROPN
fcis-9761	46	2	et	et	PROPN
fcis-9761	46	3	al	al	PROPN
fcis-9761	46	4	.	.	PUNCT
fcis-9761	47	1	[	[	X
fcis-9761	47	2	10	10	NUM
fcis-9761	47	3	]	]	PUNCT
fcis-9761	47	4	applied	apply	VERB
fcis-9761	47	5	deep	deep	ADJ
fcis-9761	47	6	convolutional	convolutional	ADJ
fcis-9761	47	7	neural	neural	ADJ
fcis-9761	47	8	networks	network	NOUN
fcis-9761	47	9	to	to	ADP
fcis-9761	47	10	dehazing	dehaze	VERB
fcis-9761	47	11	scenarios	scenario	NOUN
fcis-9761	47	12	,	,	PUNCT
fcis-9761	47	13	where	where	SCONJ
fcis-9761	47	14	their	their	PRON
fcis-9761	47	15	dehazenet	dehazenet	NOUN
fcis-9761	47	16	model	model	NOUN
fcis-9761	47	17	,	,	PUNCT
fcis-9761	47	18	established	establish	VERB
fcis-9761	47	19	using	use	VERB
fcis-9761	47	20	a	a	DET
fcis-9761	47	21	deep	deep	ADJ
fcis-9761	47	22	cnn	cnn	NOUN
fcis-9761	47	23	structure	structure	NOUN
fcis-9761	47	24	,	,	PUNCT
fcis-9761	47	25	provided	provide	VERB
fcis-9761	47	26	a	a	DET
fcis-9761	47	27	novel	novel	ADJ
fcis-9761	47	28	estimation	estimation	NOUN
fcis-9761	47	29	of	of	ADP
fcis-9761	47	30	atmospheric	atmospheric	ADJ
fcis-9761	47	31	degradation	degradation	NOUN
fcis-9761	47	32	transmission	transmission	NOUN
fcis-9761	47	33	.	.	PUNCT
fcis-9761	48	1	li	li	PROPN
fcis-9761	48	2	et	et	PROPN
fcis-9761	48	3	al	al	PROPN
fcis-9761	48	4	.	.	PUNCT
fcis-9761	49	1	[	[	X
fcis-9761	49	2	11	11	NUM
fcis-9761	49	3	]	]	PUNCT
fcis-9761	49	4	designed	design	VERB
fcis-9761	49	5	an	an	DET
fcis-9761	49	6	end	end	NOUN
fcis-9761	49	7	-	-	PUNCT
fcis-9761	49	8	to	to	ADP
fcis-9761	49	9	-	-	PUNCT
fcis-9761	49	10	end	end	NOUN
fcis-9761	49	11	aod	aod	ADJ
fcis-9761	49	12	-	-	ADJ
fcis-9761	49	13	net	net	ADJ
fcis-9761	49	14	network	network	NOUN
fcis-9761	49	15	,	,	PUNCT
fcis-9761	49	16	which	which	PRON
fcis-9761	49	17	directly	directly	ADV
fcis-9761	49	18	obtains	obtain	VERB
fcis-9761	49	19	clear	clear	ADJ
fcis-9761	49	20	images	image	NOUN
fcis-9761	49	21	without	without	ADP
fcis-9761	49	22	estimating	estimate	VERB
fcis-9761	49	23	medium	medium	ADJ
fcis-9761	49	24	transmission	transmission	NOUN
fcis-9761	49	25	and	and	CCONJ
fcis-9761	49	26	atmospheric	atmospheric	ADJ
fcis-9761	49	27	light	light	NOUN
fcis-9761	49	28	.	.	PUNCT
fcis-9761	50	1	ren	ren	NOUN
fcis-9761	50	2	et	et	PROPN
fcis-9761	50	3	al	al	PROPN
fcis-9761	50	4	.	.	PUNCT
fcis-9761	51	1	[	[	X
fcis-9761	51	2	12	12	NUM
fcis-9761	51	3	]	]	PUNCT
fcis-9761	51	4	proposed	propose	VERB
fcis-9761	51	5	the	the	DET
fcis-9761	51	6	mscnn	mscnn	PROPN
fcis-9761	51	7	algorithm	algorithm	PROPN
fcis-9761	51	8	,	,	PUNCT
fcis-9761	51	9	which	which	PRON
fcis-9761	51	10	employs	employ	VERB
fcis-9761	51	11	a	a	DET
fcis-9761	51	12	multi	multi	ADJ
fcis-9761	51	13	-	-	ADJ
fcis-9761	51	14	scale	scale	ADJ
fcis-9761	51	15	network	network	NOUN
fcis-9761	51	16	structure	structure	NOUN
fcis-9761	51	17	to	to	PART
fcis-9761	51	18	obtain	obtain	VERB
fcis-9761	51	19	clear	clear	ADJ
fcis-9761	51	20	images	image	NOUN
fcis-9761	51	21	.	.	PUNCT
fcis-9761	52	1	chen	chen	PROPN
fcis-9761	52	2	et	et	PROPN
fcis-9761	52	3	al	al	PROPN
fcis-9761	52	4	.	.	PUNCT
fcis-9761	53	1	[	[	X
fcis-9761	53	2	13	13	NUM
fcis-9761	53	3	]	]	PUNCT
fcis-9761	53	4	introduced	introduce	VERB
fcis-9761	53	5	the	the	DET
fcis-9761	53	6	gcanet	gcanet	NOUN
fcis-9761	53	7	model	model	NOUN
fcis-9761	53	8	to	to	PART
fcis-9761	53	9	address	address	VERB
fcis-9761	53	10	the	the	DET
fcis-9761	53	11	issue	issue	NOUN
fcis-9761	53	12	of	of	ADP
fcis-9761	53	13	grid	grid	NOUN
fcis-9761	53	14	artifacts	artifact	NOUN
fcis-9761	53	15	in	in	ADP
fcis-9761	53	16	the	the	DET
fcis-9761	53	17	image	image	NOUN
fcis-9761	53	18	restoration	restoration	NOUN
fcis-9761	53	19	process	process	NOUN
fcis-9761	53	20	.	.	PUNCT
fcis-9761	54	1	qin	qin	PROPN
fcis-9761	54	2	et	et	PROPN
fcis-9761	54	3	al	al	PROPN
fcis-9761	54	4	.	.	PUNCT
fcis-9761	55	1	[	[	X
fcis-9761	55	2	14	14	NUM
fcis-9761	55	3	]	]	PUNCT
fcis-9761	55	4	proposed	propose	VERB
fcis-9761	55	5	the	the	DET
fcis-9761	55	6	ffa	ffa	PROPN
fcis-9761	55	7	-	-	PUNCT
fcis-9761	55	8	net	net	ADJ
fcis-9761	55	9	model	model	NOUN
fcis-9761	55	10	,	,	PUNCT
fcis-9761	55	11	which	which	PRON
fcis-9761	55	12	incorporates	incorporate	VERB
fcis-9761	55	13	attention	attention	NOUN
fcis-9761	55	14	mechanisms	mechanism	NOUN
fcis-9761	55	15	to	to	PART
fcis-9761	55	16	effectively	effectively	ADV
fcis-9761	55	17	remove	remove	VERB
fcis-9761	55	18	non	non	ADJ
fcis-9761	55	19	-	-	ADJ
fcis-9761	55	20	uniform	uniform	ADJ
fcis-9761	55	21	haze	haze	NOUN
fcis-9761	55	22	.	.	PUNCT
fcis-9761	56	1	28	28	NUM
fcis-9761	56	2	3	3	NUM
fcis-9761	56	3	.	.	PUNCT
fcis-9761	56	4	methodology	methodology	PROPN
fcis-9761	56	5	3.1	3.1	NUM
fcis-9761	56	6	.	.	PUNCT
fcis-9761	57	1	network	network	NOUN
fcis-9761	57	2	architecture	architecture	NOUN
fcis-9761	57	3	in	in	ADP
fcis-9761	57	4	this	this	DET
fcis-9761	57	5	section	section	NOUN
fcis-9761	57	6	,	,	PUNCT
fcis-9761	57	7	we	we	PRON
fcis-9761	57	8	will	will	AUX
fcis-9761	57	9	provide	provide	VERB
fcis-9761	57	10	a	a	DET
fcis-9761	57	11	brief	brief	ADJ
fcis-9761	57	12	overview	overview	NOUN
fcis-9761	57	13	of	of	ADP
fcis-9761	57	14	the	the	DET
fcis-9761	57	15	proposed	propose	VERB
fcis-9761	57	16	network	network	NOUN
fcis-9761	57	17	,	,	PUNCT
fcis-9761	57	18	ldanet	ldanet	NOUN
fcis-9761	57	19	.	.	PUNCT
fcis-9761	58	1	as	as	SCONJ
fcis-9761	58	2	shown	show	VERB
fcis-9761	58	3	in	in	ADP
fcis-9761	58	4	figure	figure	NOUN
fcis-9761	58	5	1	1	NUM
fcis-9761	58	6	,	,	PUNCT
fcis-9761	58	7	the	the	DET
fcis-9761	58	8	network	network	NOUN
fcis-9761	58	9	takes	take	VERB
fcis-9761	58	10	a	a	DET
fcis-9761	58	11	hazy	hazy	ADJ
fcis-9761	58	12	image	image	NOUN
fcis-9761	58	13	as	as	ADP
fcis-9761	58	14	input	input	NOUN
fcis-9761	58	15	and	and	CCONJ
fcis-9761	58	16	outputs	output	VERB
fcis-9761	58	17	a	a	DET
fcis-9761	58	18	clean	clean	ADJ
fcis-9761	58	19	image	image	NOUN
fcis-9761	58	20	.	.	PUNCT
fcis-9761	59	1	the	the	DET
fcis-9761	59	2	network	network	NOUN
fcis-9761	59	3	consists	consist	VERB
fcis-9761	59	4	of	of	ADP
fcis-9761	59	5	two	two	NUM
fcis-9761	59	6	main	main	ADJ
fcis-9761	59	7	components	component	NOUN
fcis-9761	59	8	:	:	PUNCT
fcis-9761	59	9	the	the	DET
fcis-9761	59	10	dehazing	dehaze	VERB
fcis-9761	59	11	subnetwork	subnetwork	NOUN
fcis-9761	59	12	(	(	PUNCT
fcis-9761	59	13	ldsn	ldsn	NOUN
fcis-9761	59	14	)	)	PUNCT
fcis-9761	59	15	and	and	CCONJ
fcis-9761	59	16	the	the	DET
fcis-9761	59	17	image	image	NOUN
fcis-9761	59	18	enhancement	enhancement	NOUN
fcis-9761	59	19	subnetwork	subnetwork	NOUN
fcis-9761	59	20	(	(	PUNCT
fcis-9761	59	21	lesn	lesn	PROPN
fcis-9761	59	22	)	)	PUNCT
fcis-9761	59	23	.	.	PUNCT
fcis-9761	60	1	the	the	DET
fcis-9761	60	2	ldsn	ldsn	NOUN
fcis-9761	60	3	is	be	AUX
fcis-9761	60	4	designed	design	VERB
fcis-9761	60	5	as	as	ADP
fcis-9761	60	6	an	an	DET
fcis-9761	60	7	encoder	encoder	NOUN
fcis-9761	60	8	-	-	PUNCT
fcis-9761	60	9	decoder	decoder	NOUN
fcis-9761	60	10	structure	structure	NOUN
fcis-9761	60	11	to	to	PART
fcis-9761	60	12	roughly	roughly	ADV
fcis-9761	60	13	remove	remove	VERB
fcis-9761	60	14	haze	haze	NOUN
fcis-9761	60	15	from	from	ADP
fcis-9761	60	16	the	the	DET
fcis-9761	60	17	input	input	NOUN
fcis-9761	60	18	image	image	NOUN
fcis-9761	60	19	.	.	PUNCT
fcis-9761	61	1	it	it	PRON
fcis-9761	61	2	incorporates	incorporate	VERB
fcis-9761	61	3	the	the	DET
fcis-9761	61	4	tied	tie	VERB
fcis-9761	61	5	block	block	NOUN
fcis-9761	61	6	convolution	convolution	NOUN
fcis-9761	61	7	(	(	PUNCT
fcis-9761	61	8	tbc	tbc	NOUN
fcis-9761	61	9	)	)	PUNCT
fcis-9761	61	10	lightweight	lightweight	ADJ
fcis-9761	61	11	convolution	convolution	NOUN
fcis-9761	61	12	with	with	ADP
fcis-9761	61	13	shared	share	VERB
fcis-9761	61	14	parameters	parameter	NOUN
fcis-9761	61	15	,	,	PUNCT
fcis-9761	61	16	which	which	PRON
fcis-9761	61	17	significantly	significantly	ADV
fcis-9761	61	18	reduces	reduce	VERB
fcis-9761	61	19	computational	computational	ADJ
fcis-9761	61	20	and	and	CCONJ
fcis-9761	61	21	parameter	parameter	NOUN
fcis-9761	61	22	costs	cost	NOUN
fcis-9761	61	23	,	,	PUNCT
fcis-9761	61	24	saving	save	VERB
fcis-9761	61	25	time	time	NOUN
fcis-9761	61	26	and	and	CCONJ
fcis-9761	61	27	resources	resource	NOUN
fcis-9761	61	28	.	.	PUNCT
fcis-9761	62	1	this	this	DET
fcis-9761	62	2	design	design	NOUN
fcis-9761	62	3	choice	choice	NOUN
fcis-9761	62	4	is	be	AUX
fcis-9761	62	5	practical	practical	ADJ
fcis-9761	62	6	and	and	CCONJ
fcis-9761	62	7	meaningful	meaningful	ADJ
fcis-9761	62	8	.	.	PUNCT
fcis-9761	63	1	the	the	DET
fcis-9761	63	2	lesn	lesn	PROPN
fcis-9761	63	3	serves	serve	VERB
fcis-9761	63	4	as	as	ADP
fcis-9761	63	5	a	a	DET
fcis-9761	63	6	complement	complement	NOUN
fcis-9761	63	7	to	to	ADP
fcis-9761	63	8	the	the	DET
fcis-9761	63	9	ldsn	ldsn	NOUN
fcis-9761	63	10	features	feature	NOUN
fcis-9761	63	11	.	.	PUNCT
fcis-9761	64	1	it	it	PRON
fcis-9761	64	2	employs	employ	VERB
fcis-9761	64	3	the	the	DET
fcis-9761	64	4	simam	simam	ADJ
fcis-9761	64	5	attention	attention	NOUN
fcis-9761	64	6	mechanism	mechanism	NOUN
fcis-9761	64	7	to	to	PART
fcis-9761	64	8	adaptively	adaptively	ADV
fcis-9761	64	9	focus	focus	VERB
fcis-9761	64	10	on	on	ADP
fcis-9761	64	11	different	different	ADJ
fcis-9761	64	12	features	feature	NOUN
fcis-9761	64	13	and	and	CCONJ
fcis-9761	64	14	contextual	contextual	ADJ
fcis-9761	64	15	information	information	NOUN
fcis-9761	64	16	,	,	PUNCT
fcis-9761	64	17	highlighting	highlight	VERB
fcis-9761	64	18	salient	salient	NOUN
fcis-9761	64	19	features	feature	NOUN
fcis-9761	64	20	and	and	CCONJ
fcis-9761	64	21	improving	improve	VERB
fcis-9761	64	22	the	the	DET
fcis-9761	64	23	model	model	NOUN
fcis-9761	64	24	's	's	PART
fcis-9761	64	25	generalization	generalization	NOUN
fcis-9761	64	26	ability	ability	NOUN
fcis-9761	64	27	.	.	PUNCT
fcis-9761	65	1	importantly	importantly	ADV
fcis-9761	65	2	,	,	PUNCT
fcis-9761	65	3	no	no	DET
fcis-9761	65	4	additional	additional	ADJ
fcis-9761	65	5	parameters	parameter	NOUN
fcis-9761	65	6	are	be	AUX
fcis-9761	65	7	introduced	introduce	VERB
fcis-9761	65	8	in	in	ADP
fcis-9761	65	9	this	this	DET
fcis-9761	65	10	process	process	NOUN
fcis-9761	65	11	.	.	PUNCT
fcis-9761	66	1	finally	finally	ADV
fcis-9761	66	2	,	,	PUNCT
fcis-9761	66	3	through	through	ADP
fcis-9761	66	4	associative	associative	ADJ
fcis-9761	66	5	learning	learning	NOUN
fcis-9761	66	6	,	,	PUNCT
fcis-9761	66	7	the	the	DET
fcis-9761	66	8	two	two	NUM
fcis-9761	66	9	subnetworks	subnetwork	NOUN
fcis-9761	66	10	are	be	AUX
fcis-9761	66	11	trained	train	VERB
fcis-9761	66	12	to	to	PART
fcis-9761	66	13	capture	capture	VERB
fcis-9761	66	14	their	their	PRON
fcis-9761	66	15	correlation	correlation	NOUN
fcis-9761	66	16	and	and	CCONJ
fcis-9761	66	17	jointly	jointly	ADV
fcis-9761	66	18	generate	generate	VERB
fcis-9761	66	19	a	a	DET
fcis-9761	66	20	clear	clear	ADJ
fcis-9761	66	21	image	image	NOUN
fcis-9761	66	22	as	as	ADP
fcis-9761	66	23	the	the	DET
fcis-9761	66	24	final	final	ADJ
fcis-9761	66	25	output	output	NOUN
fcis-9761	66	26	.	.	PUNCT
fcis-9761	67	1	figure	figure	NOUN
fcis-9761	67	2	1	1	NUM
fcis-9761	67	3	.	.	PUNCT
fcis-9761	67	4	schematic	schematic	ADJ
fcis-9761	67	5	diagram	diagram	NOUN
fcis-9761	67	6	of	of	ADP
fcis-9761	67	7	ldanet	ldanet	NOUN
fcis-9761	67	8	3.2	3.2	NUM
fcis-9761	67	9	.	.	PUNCT
fcis-9761	68	1	loss	loss	NOUN
fcis-9761	68	2	function	function	NOUN
fcis-9761	68	3	we	we	PRON
fcis-9761	68	4	use	use	VERB
fcis-9761	68	5	charbonnier	charbonni	ADJ
fcis-9761	68	6	penalty	penalty	NOUN
fcis-9761	68	7	loss	loss	NOUN
fcis-9761	69	1	[	[	X
fcis-9761	69	2	15	15	NUM
fcis-9761	69	3	]	]	PUNCT
fcis-9761	69	4	and	and	CCONJ
fcis-9761	69	5	structural	structural	ADJ
fcis-9761	69	6	similarity	similarity	NOUN
fcis-9761	69	7	(	(	PUNCT
fcis-9761	69	8	ssim	ssim	NOUN
fcis-9761	69	9	)	)	PUNCT
fcis-9761	69	10	loss	loss	NOUN
fcis-9761	70	1	[	[	X
fcis-9761	70	2	16	16	NUM
fcis-9761	70	3	]	]	PUNCT
fcis-9761	70	4	to	to	PART
fcis-9761	70	5	jointly	jointly	ADV
fcis-9761	70	6	compute	compute	VERB
fcis-9761	70	7	the	the	DET
fcis-9761	70	8	total	total	ADJ
fcis-9761	70	9	loss	loss	NOUN
fcis-9761	70	10	function	function	NOUN
fcis-9761	70	11	for	for	ADP
fcis-9761	70	12	network	network	NOUN
fcis-9761	70	13	optimization	optimization	NOUN
fcis-9761	70	14	,	,	PUNCT
fcis-9761	70	15	aiming	aim	VERB
fcis-9761	70	16	to	to	PART
fcis-9761	70	17	more	more	ADV
fcis-9761	70	18	accurately	accurately	ADV
fcis-9761	70	19	evaluate	evaluate	VERB
fcis-9761	70	20	image	image	NOUN
fcis-9761	70	21	quality	quality	NOUN
fcis-9761	70	22	.	.	PUNCT
fcis-9761	71	1	the	the	DET
fcis-9761	71	2	mathematical	mathematical	ADJ
fcis-9761	71	3	expressions	expression	NOUN
fcis-9761	71	4	are	be	AUX
fcis-9761	71	5	as	as	SCONJ
fcis-9761	71	6	follows	follow	VERB
fcis-9761	71	7	:	:	PUNCT
fcis-9761	71	8	,	,	PUNCT
fcis-9761	71	9	(	(	PUNCT
fcis-9761	71	10	2	2	X
fcis-9761	71	11	)	)	PUNCT
fcis-9761	71	12	1	1	NUM
fcis-9761	71	13	∑	∑	ADP
fcis-9761	71	14	̂	̂	PUNCT
fcis-9761	71	15	̂	̂	X
fcis-9761	71	16	̂	̂	PUNCT
fcis-9761	71	17	̂	̂	PUNCT
fcis-9761	71	18	,	,	PUNCT
fcis-9761	71	19	(	(	PUNCT
fcis-9761	71	20	3	3	NUM
fcis-9761	71	21	)	)	PUNCT
fcis-9761	71	22	,	,	PUNCT
fcis-9761	71	23	(	(	PUNCT
fcis-9761	71	24	4	4	X
fcis-9761	71	25	)	)	PUNCT
fcis-9761	71	26	where	where	SCONJ
fcis-9761	71	27	represents	represent	VERB
fcis-9761	71	28	the	the	DET
fcis-9761	71	29	generated	generate	VERB
fcis-9761	71	30	image	image	NOUN
fcis-9761	71	31	and	and	CCONJ
fcis-9761	71	32	represents	represent	VERB
fcis-9761	71	33	the	the	DET
fcis-9761	71	34	target	target	NOUN
fcis-9761	71	35	image	image	NOUN
fcis-9761	71	36	.	.	PUNCT
fcis-9761	72	1	represents	represent	VERB
fcis-9761	72	2	the	the	DET
fcis-9761	72	3	total	total	ADJ
fcis-9761	72	4	loss	loss	NOUN
fcis-9761	72	5	function	function	NOUN
fcis-9761	72	6	,	,	PUNCT
fcis-9761	72	7	and	and	CCONJ
fcis-9761	72	8	are	be	AUX
fcis-9761	72	9	parameters	parameter	NOUN
fcis-9761	72	10	.	.	PUNCT
fcis-9761	73	1	4	4	X
fcis-9761	73	2	.	.	X
fcis-9761	73	3	experiments	experiment	NOUN
fcis-9761	73	4	4.1	4.1	NUM
fcis-9761	73	5	.	.	PUNCT
fcis-9761	74	1	datasets	dataset	NOUN
fcis-9761	74	2	to	to	PART
fcis-9761	74	3	thoroughly	thoroughly	ADV
fcis-9761	74	4	demonstrate	demonstrate	VERB
fcis-9761	74	5	the	the	DET
fcis-9761	74	6	performance	performance	NOUN
fcis-9761	74	7	of	of	ADP
fcis-9761	74	8	the	the	DET
fcis-9761	74	9	proposed	propose	VERB
fcis-9761	74	10	model	model	NOUN
fcis-9761	74	11	,	,	PUNCT
fcis-9761	74	12	we	we	PRON
fcis-9761	74	13	conducted	conduct	VERB
fcis-9761	74	14	experiments	experiment	NOUN
fcis-9761	74	15	on	on	ADP
fcis-9761	74	16	several	several	ADJ
fcis-9761	74	17	dehazing	dehaze	VERB
fcis-9761	74	18	datasets	dataset	NOUN
fcis-9761	74	19	,	,	PUNCT
fcis-9761	74	20	including	include	VERB
fcis-9761	74	21	synthetic	synthetic	ADJ
fcis-9761	74	22	datasets	dataset	NOUN
fcis-9761	74	23	and	and	CCONJ
fcis-9761	74	24	heterogeneous	heterogeneous	ADJ
fcis-9761	74	25	datasets	dataset	NOUN
fcis-9761	74	26	.	.	PUNCT
fcis-9761	75	1	the	the	DET
fcis-9761	75	2	synthetic	synthetic	ADJ
fcis-9761	75	3	dataset	dataset	NOUN
fcis-9761	75	4	utilized	utilize	VERB
fcis-9761	75	5	the	the	DET
fcis-9761	75	6	reside	reside	NOUN
fcis-9761	75	7	dataset	dataset	NOUN
fcis-9761	75	8	[	[	X
fcis-9761	75	9	17	17	NUM
fcis-9761	75	10	]	]	PUNCT
fcis-9761	75	11	,	,	PUNCT
fcis-9761	75	12	which	which	PRON
fcis-9761	75	13	is	be	AUX
fcis-9761	75	14	widely	widely	ADV
fcis-9761	75	15	used	use	VERB
fcis-9761	75	16	in	in	ADP
fcis-9761	75	17	the	the	DET
fcis-9761	75	18	field	field	NOUN
fcis-9761	75	19	of	of	ADP
fcis-9761	75	20	image	image	NOUN
fcis-9761	75	21	dehazing	dehazing	NOUN
fcis-9761	75	22	and	and	CCONJ
fcis-9761	75	23	consists	consist	VERB
fcis-9761	75	24	of	of	ADP
fcis-9761	75	25	haze	haze	NOUN
fcis-9761	75	26	images	image	NOUN
fcis-9761	75	27	synthesized	synthesize	VERB
fcis-9761	75	28	using	use	VERB
fcis-9761	75	29	prior	prior	ADJ
fcis-9761	75	30	information	information	NOUN
fcis-9761	75	31	.	.	PUNCT
fcis-9761	76	1	it	it	PRON
fcis-9761	76	2	consists	consist	VERB
fcis-9761	76	3	of	of	ADP
fcis-9761	76	4	indoor	indoor	ADJ
fcis-9761	76	5	training	training	NOUN
fcis-9761	76	6	set	set	NOUN
fcis-9761	76	7	(	(	PUNCT
fcis-9761	76	8	its	its	PRON
fcis-9761	76	9	)	)	PUNCT
fcis-9761	76	10	,	,	PUNCT
fcis-9761	76	11	outdoor	outdoor	ADJ
fcis-9761	76	12	training	training	NOUN
fcis-9761	76	13	set	set	NOUN
fcis-9761	76	14	(	(	PUNCT
fcis-9761	76	15	ots	ots	PROPN
fcis-9761	76	16	)	)	PUNCT
fcis-9761	76	17	,	,	PUNCT
fcis-9761	76	18	and	and	CCONJ
fcis-9761	76	19	testing	testing	NOUN
fcis-9761	76	20	set	set	NOUN
fcis-9761	76	21	(	(	PUNCT
fcis-9761	76	22	sots	sot	NOUN
fcis-9761	76	23	)	)	PUNCT
fcis-9761	76	24	.	.	PUNCT
fcis-9761	77	1	the	the	DET
fcis-9761	77	2	proposed	propose	VERB
fcis-9761	77	3	model	model	NOUN
fcis-9761	77	4	not	not	PART
fcis-9761	77	5	only	only	ADV
fcis-9761	77	6	showed	show	VERB
fcis-9761	77	7	superior	superior	ADJ
fcis-9761	77	8	results	result	NOUN
fcis-9761	77	9	on	on	ADP
fcis-9761	77	10	the	the	DET
fcis-9761	77	11	synthetic	synthetic	ADJ
fcis-9761	77	12	dataset	dataset	NOUN
fcis-9761	77	13	but	but	CCONJ
fcis-9761	77	14	,	,	PUNCT
fcis-9761	77	15	more	more	ADV
fcis-9761	77	16	importantly	importantly	ADV
fcis-9761	77	17	,	,	PUNCT
fcis-9761	77	18	achieved	achieve	VERB
fcis-9761	77	19	satisfactory	satisfactory	ADJ
fcis-9761	77	20	performance	performance	NOUN
fcis-9761	77	21	on	on	ADP
fcis-9761	77	22	the	the	DET
fcis-9761	77	23	heterogeneous	heterogeneous	ADJ
fcis-9761	77	24	dehazing	dehazing	NOUN
fcis-9761	77	25	datasets	dataset	NOUN
fcis-9761	77	26	.	.	PUNCT
fcis-9761	78	1	therefore	therefore	ADV
fcis-9761	78	2	,	,	PUNCT
fcis-9761	78	3	we	we	PRON
fcis-9761	78	4	conducted	conduct	VERB
fcis-9761	78	5	experiments	experiment	NOUN
fcis-9761	78	6	and	and	CCONJ
fcis-9761	78	7	comparisons	comparison	NOUN
fcis-9761	78	8	on	on	ADP
fcis-9761	78	9	the	the	DET
fcis-9761	78	10	i	i	NOUN
fcis-9761	78	11	-	-	PUNCT
fcis-9761	78	12	haze	haze	NOUN
fcis-9761	79	1	[	[	X
fcis-9761	79	2	18	18	NUM
fcis-9761	79	3	]	]	PUNCT
fcis-9761	79	4	,	,	PUNCT
fcis-9761	79	5	o	o	NOUN
fcis-9761	79	6	-	-	NOUN
fcis-9761	79	7	haze	haze	NOUN
fcis-9761	79	8	[	[	X
fcis-9761	79	9	19	19	NUM
fcis-9761	79	10	]	]	PUNCT
fcis-9761	79	11	,	,	PUNCT
fcis-9761	79	12	and	and	CCONJ
fcis-9761	79	13	nh	nh	NOUN
fcis-9761	79	14	-	-	PUNCT
fcis-9761	79	15	haze	haze	NOUN
fcis-9761	79	16	[	[	X
fcis-9761	79	17	20	20	NUM
fcis-9761	79	18	]	]	PUNCT
fcis-9761	79	19	datasets	dataset	NOUN
fcis-9761	79	20	.	.	PUNCT
fcis-9761	80	1	4.2	4.2	NUM
fcis-9761	80	2	.	.	PUNCT
fcis-9761	81	1	quality	quality	NOUN
fcis-9761	81	2	evaluation	evaluation	NOUN
fcis-9761	81	3	metrics	metric	NOUN
fcis-9761	81	4	in	in	ADP
fcis-9761	81	5	the	the	DET
fcis-9761	81	6	field	field	NOUN
fcis-9761	81	7	of	of	ADP
fcis-9761	81	8	image	image	NOUN
fcis-9761	81	9	dehazing	dehazing	NOUN
fcis-9761	81	10	,	,	PUNCT
fcis-9761	81	11	it	it	PRON
fcis-9761	81	12	is	be	AUX
fcis-9761	81	13	crucial	crucial	ADJ
fcis-9761	81	14	to	to	PART
fcis-9761	81	15	objectively	objectively	ADV
fcis-9761	81	16	evaluate	evaluate	VERB
fcis-9761	81	17	the	the	DET
fcis-9761	81	18	performance	performance	NOUN
fcis-9761	81	19	of	of	ADP
fcis-9761	81	20	an	an	DET
fcis-9761	81	21	algorithm	algorithm	NOUN
fcis-9761	81	22	.	.	PUNCT
fcis-9761	82	1	evaluating	evaluate	VERB
fcis-9761	82	2	the	the	DET
fcis-9761	82	3	performance	performance	NOUN
fcis-9761	82	4	of	of	ADP
fcis-9761	82	5	an	an	DET
fcis-9761	82	6	image	image	NOUN
fcis-9761	82	7	dehazing	dehazing	NOUN
fcis-9761	82	8	algorithm	algorithm	NOUN
fcis-9761	82	9	typically	typically	ADV
fcis-9761	82	10	involves	involve	VERB
fcis-9761	82	11	various	various	ADJ
fcis-9761	82	12	evaluation	evaluation	NOUN
fcis-9761	82	13	metrics	metric	NOUN
fcis-9761	82	14	.	.	PUNCT
fcis-9761	83	1	in	in	ADP
fcis-9761	83	2	this	this	DET
fcis-9761	83	3	paper	paper	NOUN
fcis-9761	83	4	,	,	PUNCT
fcis-9761	83	5	we	we	PRON
fcis-9761	83	6	used	use	VERB
fcis-9761	83	7	peak	peak	NOUN
fcis-9761	83	8	signal	signal	NOUN
fcis-9761	83	9	-	-	PUNCT
fcis-9761	83	10	to	to	ADP
fcis-9761	83	11	-	-	PUNCT
fcis-9761	83	12	noise	noise	NOUN
fcis-9761	83	13	ratio	ratio	NOUN
fcis-9761	83	14	(	(	PUNCT
fcis-9761	83	15	psnr	psnr	NOUN
fcis-9761	83	16	)	)	PUNCT
fcis-9761	84	1	[	[	X
fcis-9761	84	2	21	21	NUM
fcis-9761	84	3	]	]	PUNCT
fcis-9761	84	4	and	and	CCONJ
fcis-9761	84	5	structural	structural	ADJ
fcis-9761	84	6	similarity	similarity	NOUN
fcis-9761	84	7	index	index	NOUN
fcis-9761	84	8	(	(	PUNCT
fcis-9761	84	9	ssim	ssim	NOUN
fcis-9761	84	10	)	)	PUNCT
fcis-9761	85	1	[	[	X
fcis-9761	85	2	22	22	NUM
fcis-9761	85	3	]	]	PUNCT
fcis-9761	85	4	to	to	PART
fcis-9761	85	5	measure	measure	VERB
fcis-9761	85	6	the	the	DET
fcis-9761	85	7	reconstruction	reconstruction	NOUN
fcis-9761	85	8	quality	quality	NOUN
fcis-9761	85	9	of	of	ADP
fcis-9761	85	10	the	the	DET
fcis-9761	85	11	images	image	NOUN
fcis-9761	85	12	.	.	PUNCT
fcis-9761	86	1	the	the	DET
fcis-9761	86	2	psnr	psnr	NOUN
fcis-9761	86	3	value	value	NOUN
fcis-9761	86	4	reflects	reflect	VERB
fcis-9761	86	5	the	the	DET
fcis-9761	86	6	difference	difference	NOUN
fcis-9761	86	7	between	between	ADP
fcis-9761	86	8	the	the	DET
fcis-9761	86	9	original	original	ADJ
fcis-9761	86	10	image	image	NOUN
fcis-9761	86	11	and	and	CCONJ
fcis-9761	86	12	the	the	DET
fcis-9761	86	13	reconstructed	reconstructed	ADJ
fcis-9761	86	14	image	image	NOUN
fcis-9761	86	15	,	,	PUNCT
fcis-9761	86	16	where	where	SCONJ
fcis-9761	86	17	a	a	DET
fcis-9761	86	18	higher	high	ADJ
fcis-9761	86	19	value	value	NOUN
fcis-9761	86	20	indicates	indicate	VERB
fcis-9761	86	21	better	well	ADJ
fcis-9761	86	22	image	image	NOUN
fcis-9761	86	23	restoration	restoration	NOUN
fcis-9761	86	24	.	.	PUNCT
fcis-9761	87	1	ssim	ssim	NOUN
fcis-9761	87	2	measures	measure	VERB
fcis-9761	87	3	the	the	DET
fcis-9761	87	4	similarity	similarity	NOUN
fcis-9761	87	5	between	between	ADP
fcis-9761	87	6	the	the	DET
fcis-9761	87	7	original	original	ADJ
fcis-9761	87	8	image	image	NOUN
fcis-9761	87	9	and	and	CCONJ
fcis-9761	87	10	the	the	DET
fcis-9761	87	11	reconstructed	reconstructed	ADJ
fcis-9761	87	12	image	image	NOUN
fcis-9761	87	13	by	by	ADP
fcis-9761	87	14	comparing	compare	VERB
fcis-9761	87	15	their	their	PRON
fcis-9761	87	16	contrast	contrast	NOUN
fcis-9761	87	17	and	and	CCONJ
fcis-9761	87	18	structural	structural	ADJ
fcis-9761	87	19	information	information	NOUN
fcis-9761	87	20	.	.	PUNCT
fcis-9761	88	1	the	the	DET
fcis-9761	88	2	ssim	ssim	NOUN
fcis-9761	88	3	value	value	NOUN
fcis-9761	88	4	ranges	range	VERB
fcis-9761	88	5	from	from	ADP
fcis-9761	88	6	0	0	NUM
fcis-9761	88	7	to	to	ADP
fcis-9761	88	8	1	1	NUM
fcis-9761	88	9	,	,	PUNCT
fcis-9761	88	10	with	with	ADP
fcis-9761	88	11	a	a	DET
fcis-9761	88	12	value	value	NOUN
fcis-9761	88	13	closer	close	ADV
fcis-9761	88	14	to	to	ADP
fcis-9761	88	15	1	1	NUM
fcis-9761	88	16	indicating	indicate	VERB
fcis-9761	88	17	higher	high	ADJ
fcis-9761	88	18	image	image	NOUN
fcis-9761	88	19	similarity	similarity	NOUN
fcis-9761	88	20	and	and	CCONJ
fcis-9761	88	21	better	well	ADJ
fcis-9761	88	22	image	image	NOUN
fcis-9761	88	23	restoration	restoration	NOUN
fcis-9761	88	24	.	.	PUNCT
fcis-9761	89	1	4.3	4.3	NUM
fcis-9761	89	2	.	.	PUNCT
fcis-9761	89	3	experimental	experimental	ADJ
fcis-9761	89	4	results	result	NOUN
fcis-9761	89	5	and	and	CCONJ
fcis-9761	89	6	analysis	analysis	NOUN
fcis-9761	89	7	table	table	NOUN
fcis-9761	89	8	1	1	NUM
fcis-9761	89	9	summarizes	summarize	VERB
fcis-9761	89	10	the	the	DET
fcis-9761	89	11	image	image	NOUN
fcis-9761	89	12	quality	quality	NOUN
fcis-9761	89	13	evaluation	evaluation	NOUN
fcis-9761	89	14	metrics	metric	NOUN
fcis-9761	89	15	of	of	ADP
fcis-9761	89	16	our	our	PRON
fcis-9761	89	17	proposed	propose	VERB
fcis-9761	89	18	method	method	NOUN
fcis-9761	89	19	compared	compare	VERB
fcis-9761	89	20	to	to	ADP
fcis-9761	89	21	dcp	dcp	PROPN
fcis-9761	89	22	,	,	PUNCT
fcis-9761	89	23	ffanet	ffanet	NOUN
fcis-9761	89	24	,	,	PUNCT
fcis-9761	89	25	and	and	CCONJ
fcis-9761	89	26	msbdn	msbdn	PROPN
fcis-9761	89	27	methods	method	NOUN
fcis-9761	89	28	on	on	ADP
fcis-9761	89	29	sots	sot	NOUN
fcis-9761	89	30	,	,	PUNCT
fcis-9761	89	31	i	i	PRON
fcis-9761	89	32	-	-	PUNCT
fcis-9761	89	33	haze	haze	VERB
fcis-9761	89	34	,	,	PUNCT
fcis-9761	89	35	o	o	NOUN
fcis-9761	89	36	-	-	NOUN
fcis-9761	89	37	haze	haze	NOUN
fcis-9761	89	38	,	,	PUNCT
fcis-9761	89	39	and	and	CCONJ
fcis-9761	89	40	nhhaze	nhhaze	VERB
fcis-9761	89	41	datasets	dataset	NOUN
fcis-9761	89	42	.	.	PUNCT
fcis-9761	90	1	each	each	DET
fcis-9761	90	2	value	value	NOUN
fcis-9761	90	3	in	in	ADP
fcis-9761	90	4	the	the	DET
fcis-9761	90	5	table	table	NOUN
fcis-9761	90	6	represents	represent	VERB
fcis-9761	90	7	the	the	DET
fcis-9761	90	8	average	average	ADJ
fcis-9761	90	9	result	result	NOUN
fcis-9761	90	10	of	of	ADP
fcis-9761	90	11	the	the	DET
fcis-9761	90	12	tests	test	NOUN
fcis-9761	90	13	.	.	PUNCT
fcis-9761	91	1	it	it	PRON
fcis-9761	91	2	is	be	AUX
fcis-9761	91	3	evident	evident	ADJ
fcis-9761	91	4	that	that	SCONJ
fcis-9761	91	5	our	our	PRON
fcis-9761	91	6	proposed	propose	VERB
fcis-9761	91	7	method	method	NOUN
fcis-9761	91	8	outperforms	outperform	VERB
fcis-9761	91	9	the	the	DET
fcis-9761	91	10	other	other	ADJ
fcis-9761	91	11	methods	method	NOUN
fcis-9761	91	12	by	by	ADP
fcis-9761	91	13	a	a	DET
fcis-9761	91	14	significant	significant	ADJ
fcis-9761	91	15	margin	margin	NOUN
fcis-9761	91	16	in	in	ADP
fcis-9761	91	17	terms	term	NOUN
fcis-9761	91	18	of	of	ADP
fcis-9761	91	19	numerical	numerical	ADJ
fcis-9761	91	20	values	value	NOUN
fcis-9761	91	21	.	.	PUNCT
fcis-9761	92	1	table	table	NOUN
fcis-9761	92	2	1	1	NUM
fcis-9761	92	3	.	.	PUNCT
fcis-9761	92	4	comparison	comparison	NOUN
fcis-9761	92	5	of	of	ADP
fcis-9761	92	6	image	image	NOUN
fcis-9761	92	7	quality	quality	NOUN
fcis-9761	92	8	evaluation	evaluation	NOUN
fcis-9761	92	9	metrics	metric	NOUN
fcis-9761	92	10	on	on	ADP
fcis-9761	92	11	sots	sot	NOUN
fcis-9761	92	12	,	,	PUNCT
fcis-9761	92	13	i	i	PRON
fcis-9761	92	14	-	-	PUNCT
fcis-9761	92	15	haze	haze	VERB
fcis-9761	92	16	,	,	PUNCT
fcis-9761	92	17	o	o	NOUN
fcis-9761	92	18	-	-	NOUN
fcis-9761	92	19	haze	haze	NOUN
fcis-9761	92	20	and	and	CCONJ
fcis-9761	92	21	nh	nh	NOUN
fcis-9761	92	22	-	-	PUNCT
fcis-9761	92	23	haze	haze	NOUN
fcis-9761	92	24	datasets	dataset	NOUN
fcis-9761	92	25	,	,	PUNCT
fcis-9761	92	26	where	where	SCONJ
fcis-9761	92	27	↑	↑	PROPN
fcis-9761	92	28	indicates	indicate	VERB
fcis-9761	92	29	a	a	DET
fcis-9761	92	30	better	well	ADJ
fcis-9761	92	31	value	value	NOUN
fcis-9761	92	32	as	as	SCONJ
fcis-9761	92	33	it	it	PRON
fcis-9761	92	34	increases	increase	VERB
fcis-9761	92	35	,	,	PUNCT
fcis-9761	92	36	bold	bold	ADJ
fcis-9761	92	37	means	mean	VERB
fcis-9761	92	38	the	the	DET
fcis-9761	92	39	optimal	optimal	ADJ
fcis-9761	92	40	results	result	NOUN
fcis-9761	92	41	dataset	dataset	VERB
fcis-9761	92	42	metric	metric	ADJ
fcis-9761	92	43	dcp	dcp	PROPN
fcis-9761	92	44	ffanet	ffanet	PROPN
fcis-9761	92	45	msbdn	msbdn	PROPN
fcis-9761	92	46	ours	ours	PRON
fcis-9761	92	47	sots	sot	NOUN
fcis-9761	92	48	ssim↑	ssim↑	VERB
fcis-9761	92	49	0.832	0.832	NUM
fcis-9761	92	50	0.944	0.944	NUM
fcis-9761	92	51	0.927	0.927	NUM
fcis-9761	92	52	0.967	0.967	NUM
fcis-9761	92	53	psnr↑	psnr↑	NOUN
fcis-9761	92	54	16.98	16.98	NUM
fcis-9761	92	55	31.37	31.37	NUM
fcis-9761	92	56	29.53	29.53	NUM
fcis-9761	92	57	28.29	28.29	NUM
fcis-9761	92	58	i	i	PROPN
fcis-9761	92	59	-	-	PUNCT
fcis-9761	92	60	haze	haze	NOUN
fcis-9761	92	61	ssim↑	ssim↑	VERB
fcis-9761	92	62	0.651	0.651	NUM
fcis-9761	92	63	0.663	0.663	NUM
fcis-9761	92	64	0.739	0.739	NUM
fcis-9761	92	65	0.806	0.806	NUM
fcis-9761	92	66	psnr↑	psnr↑	NOUN
fcis-9761	92	67	12.94	12.94	NUM
fcis-9761	92	68	16.28	16.28	NUM
fcis-9761	92	69	16.29	16.29	NUM
fcis-9761	92	70	19.28	19.28	NUM
fcis-9761	92	71	o	o	NOUN
fcis-9761	92	72	-	-	NOUN
fcis-9761	92	73	haze	haze	NOUN
fcis-9761	92	74	ssim↑	ssim↑	VERB
fcis-9761	92	75	0.575	0.575	NUM
fcis-9761	92	76	0.719	0.719	NUM
fcis-9761	92	77	0.639	0.639	NUM
fcis-9761	92	78	0.856	0.856	NUM
fcis-9761	92	79	psnr↑	psnr↑	NOUN
fcis-9761	92	80	16.17	16.17	NUM
fcis-9761	92	81	18.27	18.27	NUM
fcis-9761	92	82	18.38	18.38	NUM
fcis-9761	92	83	24.08	24.08	NUM
fcis-9761	92	84	nhhaze	nhhaze	NOUN
fcis-9761	92	85	ssim↑	ssim↑	NOUN
fcis-9761	92	86	0.53	0.53	NUM
fcis-9761	92	87	0.602	0.602	NUM
fcis-9761	92	88	0.658	0.658	NUM
fcis-9761	92	89	0.709	0.709	NUM
fcis-9761	92	90	psnr↑	psnr↑	NOUN
fcis-9761	92	91	13.01	13.01	NUM
fcis-9761	92	92	15.57	15.57	NUM
fcis-9761	92	93	17.46	17.46	NUM
fcis-9761	92	94	17.77	17.77	NUM
fcis-9761	92	95	efficiency	efficiency	NOUN
fcis-9761	92	96	flops↓	flops↓	PROPN
fcis-9761	92	97	—	—	PUNCT
fcis-9761	92	98	288.3	288.3	NUM
fcis-9761	92	99	g	g	NOUN
fcis-9761	92	100	41.5	41.5	NUM
fcis-9761	92	101	g	g	NOUN
fcis-9761	92	102	4.2	4.2	NUM
fcis-9761	92	103	params↓	params↓	NOUN
fcis-9761	92	104	—	—	PUNCT
fcis-9761	92	105	4.46	4.46	NUM
fcis-9761	92	106	m	m	NUM
fcis-9761	92	107	31.35	31.35	NUM
fcis-9761	92	108	m	m	NOUN
fcis-9761	92	109	0.26k	0.26k	NOUN
fcis-9761	92	110	figures	figure	NOUN
fcis-9761	92	111	2	2	NUM
fcis-9761	92	112	-	-	SYM
fcis-9761	92	113	5	5	NUM
fcis-9761	92	114	compare	compare	VERB
fcis-9761	92	115	the	the	DET
fcis-9761	92	116	results	result	NOUN
fcis-9761	92	117	of	of	ADP
fcis-9761	92	118	our	our	PRON
fcis-9761	92	119	method	method	NOUN
fcis-9761	92	120	and	and	CCONJ
fcis-9761	92	121	other	other	ADJ
fcis-9761	92	122	methods	method	NOUN
fcis-9761	92	123	on	on	ADP
fcis-9761	92	124	sots	sot	NOUN
fcis-9761	92	125	,	,	PUNCT
fcis-9761	92	126	i	i	PRON
fcis-9761	92	127	-	-	PUNCT
fcis-9761	92	128	haze	haze	VERB
fcis-9761	92	129	,	,	PUNCT
fcis-9761	92	130	o	o	NOUN
fcis-9761	92	131	-	-	NOUN
fcis-9761	92	132	haze	haze	NOUN
fcis-9761	92	133	,	,	PUNCT
fcis-9761	92	134	and	and	CCONJ
fcis-9761	92	135	nh	nh	NOUN
fcis-9761	92	136	-	-	PUNCT
fcis-9761	92	137	haze	haze	NOUN
fcis-9761	92	138	datasets	dataset	NOUN
fcis-9761	92	139	,	,	PUNCT
fcis-9761	92	140	which	which	PRON
fcis-9761	92	141	are	be	AUX
fcis-9761	92	142	visually	visually	ADV
fcis-9761	92	143	more	more	ADV
fcis-9761	92	144	evident	evident	ADJ
fcis-9761	92	145	.	.	PUNCT
fcis-9761	93	1	due	due	ADP
fcis-9761	93	2	to	to	ADP
fcis-9761	93	3	the	the	DET
fcis-9761	93	4	nonuniformity	nonuniformity	NOUN
fcis-9761	93	5	of	of	ADP
fcis-9761	93	6	fog	fog	NOUN
fcis-9761	93	7	in	in	ADP
fcis-9761	93	8	the	the	DET
fcis-9761	93	9	images	image	NOUN
fcis-9761	93	10	,	,	PUNCT
fcis-9761	93	11	it	it	PRON
fcis-9761	93	12	means	mean	VERB
fcis-9761	93	13	that	that	SCONJ
fcis-9761	93	14	different	different	ADJ
fcis-9761	93	15	regions	region	NOUN
fcis-9761	93	16	have	have	VERB
fcis-9761	93	17	varying	vary	VERB
fcis-9761	93	18	degrees	degree	NOUN
fcis-9761	93	19	of	of	ADP
fcis-9761	93	20	scattering	scattering	NOUN
fcis-9761	93	21	,	,	PUNCT
fcis-9761	93	22	making	make	VERB
fcis-9761	93	23	it	it	PRON
fcis-9761	93	24	challenging	challenge	VERB
fcis-9761	93	25	for	for	ADP
fcis-9761	93	26	traditional	traditional	ADJ
fcis-9761	93	27	methods	method	NOUN
fcis-9761	93	28	to	to	PART
fcis-9761	93	29	obtain	obtain	VERB
fcis-9761	93	30	accurate	accurate	ADJ
fcis-9761	93	31	transmission	transmission	NOUN
fcis-9761	93	32	images	image	NOUN
fcis-9761	93	33	.	.	PUNCT
fcis-9761	94	1	it	it	PRON
fcis-9761	94	2	is	be	AUX
fcis-9761	94	3	evident	evident	ADJ
fcis-9761	94	4	that	that	SCONJ
fcis-9761	94	5	when	when	SCONJ
fcis-9761	94	6	dcp	dcp	NOUN
fcis-9761	94	7	processes	process	VERB
fcis-9761	94	8	heavily	heavily	ADV
fcis-9761	94	9	hazy	hazy	ADJ
fcis-9761	94	10	images	image	NOUN
fcis-9761	94	11	,	,	PUNCT
fcis-9761	94	12	the	the	DET
fcis-9761	94	13	resulting	result	VERB
fcis-9761	94	14	images	image	NOUN
fcis-9761	94	15	are	be	AUX
fcis-9761	94	16	often	often	ADV
fcis-9761	94	17	darker	dark	ADJ
fcis-9761	94	18	than	than	ADP
fcis-9761	94	19	the	the	DET
fcis-9761	94	20	ground	ground	NOUN
fcis-9761	94	21	truth	truth	NOUN
fcis-9761	94	22	,	,	PUNCT
fcis-9761	94	23	affecting	affect	VERB
fcis-9761	94	24	the	the	DET
fcis-9761	94	25	visual	visual	ADJ
fcis-9761	94	26	effect	effect	NOUN
fcis-9761	94	27	.	.	PUNCT
fcis-9761	95	1	ffa	ffa	PROPN
fcis-9761	95	2	-	-	PUNCT
fcis-9761	95	3	net	net	NOUN
fcis-9761	95	4	can	can	AUX
fcis-9761	95	5	effectively	effectively	ADV
fcis-9761	95	6	remove	remove	VERB
fcis-9761	95	7	non	non	ADJ
fcis-9761	95	8	-	-	ADJ
fcis-9761	95	9	uniform	uniform	ADJ
fcis-9761	95	10	fog	fog	PROPN
fcis-9761	95	11	,	,	PUNCT
fcis-9761	95	12	but	but	CCONJ
fcis-9761	95	13	the	the	DET
fcis-9761	95	14	resulting	result	VERB
fcis-9761	95	15	images	image	NOUN
fcis-9761	95	16	may	may	AUX
fcis-9761	95	17	have	have	VERB
fcis-9761	95	18	halos	halo	NOUN
fcis-9761	95	19	and	and	CCONJ
fcis-9761	95	20	artifacts	artifact	NOUN
fcis-9761	95	21	.	.	PUNCT
fcis-9761	96	1	msbdn	msbdn	PROPN
fcis-9761	96	2	exhibits	exhibit	VERB
fcis-9761	96	3	local	local	ADJ
fcis-9761	96	4	color	color	NOUN
fcis-9761	96	5	distortion	distortion	NOUN
fcis-9761	96	6	and	and	CCONJ
fcis-9761	96	7	poor	poor	ADJ
fcis-9761	96	8	stability	stability	NOUN
fcis-9761	96	9	,	,	PUNCT
fcis-9761	96	10	with	with	ADP
fcis-9761	96	11	residual	residual	ADJ
fcis-9761	96	12	haze	haze	NOUN
fcis-9761	96	13	still	still	ADV
fcis-9761	96	14	present	present	ADJ
fcis-9761	96	15	.	.	PUNCT
fcis-9761	97	1	in	in	ADP
fcis-9761	97	2	contrast	contrast	NOUN
fcis-9761	97	3	,	,	PUNCT
fcis-9761	97	4	our	our	PRON
fcis-9761	97	5	method	method	NOUN
fcis-9761	97	6	can	can	AUX
fcis-9761	97	7	capture	capture	VERB
fcis-9761	97	8	rich	rich	ADJ
fcis-9761	97	9	details	detail	NOUN
fcis-9761	97	10	and	and	CCONJ
fcis-9761	97	11	local	local	ADJ
fcis-9761	97	12	features	feature	NOUN
fcis-9761	97	13	,	,	PUNCT
fcis-9761	97	14	effectively	effectively	ADV
fcis-9761	97	15	handling	handle	VERB
fcis-9761	97	16	heterogeneous	heterogeneous	ADJ
fcis-9761	97	17	haze	haze	NOUN
fcis-9761	97	18	and	and	CCONJ
fcis-9761	97	19	achieving	achieve	VERB
fcis-9761	97	20	superior	superior	ADJ
fcis-9761	97	21	haze	haze	NOUN
fcis-9761	97	22	removal	removal	NOUN
fcis-9761	97	23	results	result	NOUN
fcis-9761	97	24	.	.	PUNCT
fcis-9761	98	1	29	29	NUM
fcis-9761	98	2	figure	figure	NOUN
fcis-9761	98	3	2	2	NUM
fcis-9761	98	4	.	.	PUNCT
fcis-9761	98	5	visualized	visualize	VERB
fcis-9761	98	6	results	result	NOUN
fcis-9761	98	7	on	on	ADP
fcis-9761	98	8	sots	sot	NOUN
fcis-9761	98	9	(	(	PUNCT
fcis-9761	98	10	outdoor	outdoor	ADJ
fcis-9761	98	11	)	)	PUNCT
fcis-9761	98	12	dataset	dataset	NOUN
fcis-9761	98	13	figure	figure	NOUN
fcis-9761	98	14	3	3	NUM
fcis-9761	98	15	.	.	PUNCT
fcis-9761	98	16	visualized	visualize	VERB
fcis-9761	98	17	results	result	NOUN
fcis-9761	98	18	on	on	ADP
fcis-9761	98	19	i	i	NOUN
fcis-9761	98	20	-	-	PUNCT
fcis-9761	98	21	haze	haze	NOUN
fcis-9761	98	22	dataset	dataset	NOUN
fcis-9761	98	23	figure	figure	NOUN
fcis-9761	98	24	4	4	NUM
fcis-9761	98	25	.	.	PUNCT
fcis-9761	98	26	visualized	visualize	VERB
fcis-9761	98	27	results	result	NOUN
fcis-9761	98	28	on	on	ADP
fcis-9761	98	29	o	o	ADJ
fcis-9761	98	30	-	-	ADJ
fcis-9761	98	31	haze	haze	ADJ
fcis-9761	98	32	dataset	dataset	NOUN
fcis-9761	98	33	figure	figure	NOUN
fcis-9761	98	34	5	5	NUM
fcis-9761	98	35	.	.	PUNCT
fcis-9761	98	36	visualized	visualize	VERB
fcis-9761	98	37	results	result	NOUN
fcis-9761	98	38	on	on	ADP
fcis-9761	98	39	nh	nh	NOUN
fcis-9761	98	40	-	-	PUNCT
fcis-9761	98	41	haze	haze	NOUN
fcis-9761	98	42	dataset	dataset	NOUN
fcis-9761	98	43	5	5	NUM
fcis-9761	98	44	.	.	PUNCT
fcis-9761	98	45	conclusion	conclusion	NOUN
fcis-9761	98	46	inspired	inspire	VERB
fcis-9761	98	47	by	by	ADP
fcis-9761	98	48	deep	deep	ADJ
fcis-9761	98	49	learning	learning	NOUN
fcis-9761	98	50	and	and	CCONJ
fcis-9761	98	51	influenced	influence	VERB
fcis-9761	98	52	by	by	ADP
fcis-9761	98	53	popular	popular	ADJ
fcis-9761	98	54	neural	neural	ADJ
fcis-9761	98	55	networks	network	NOUN
fcis-9761	99	1	,	,	PUNCT
fcis-9761	99	2	this	this	DET
fcis-9761	99	3	paper	paper	NOUN
fcis-9761	99	4	proposes	propose	VERB
fcis-9761	99	5	a	a	DET
fcis-9761	99	6	lightweight	lightweight	ADJ
fcis-9761	99	7	dual	dual	ADJ
fcis-9761	99	8	-	-	PUNCT
fcis-9761	99	9	branch	branch	NOUN
fcis-9761	99	10	image	image	NOUN
fcis-9761	99	11	dehazing	dehazing	NOUN
fcis-9761	99	12	network	network	NOUN
fcis-9761	99	13	based	base	VERB
fcis-9761	99	14	on	on	ADP
fcis-9761	99	15	correlation	correlation	NOUN
fcis-9761	99	16	learning	learn	VERB
fcis-9761	99	17	to	to	PART
fcis-9761	99	18	eliminate	eliminate	VERB
fcis-9761	99	19	the	the	DET
fcis-9761	99	20	effects	effect	NOUN
fcis-9761	99	21	of	of	ADP
fcis-9761	99	22	haze	haze	NOUN
fcis-9761	99	23	in	in	ADP
fcis-9761	99	24	images	image	NOUN
fcis-9761	99	25	and	and	CCONJ
fcis-9761	99	26	improve	improve	VERB
fcis-9761	99	27	the	the	DET
fcis-9761	99	28	usability	usability	NOUN
fcis-9761	99	29	of	of	ADP
fcis-9761	99	30	systems	system	NOUN
fcis-9761	99	31	in	in	ADP
fcis-9761	99	32	domains	domain	NOUN
fcis-9761	99	33	such	such	ADJ
fcis-9761	99	34	as	as	ADP
fcis-9761	99	35	transportation	transportation	NOUN
fcis-9761	99	36	,	,	PUNCT
fcis-9761	99	37	surveillance	surveillance	NOUN
fcis-9761	99	38	,	,	PUNCT
fcis-9761	99	39	and	and	CCONJ
fcis-9761	99	40	aviation	aviation	NOUN
fcis-9761	99	41	.	.	PUNCT
fcis-9761	100	1	specifically	specifically	ADV
fcis-9761	100	2	,	,	PUNCT
fcis-9761	100	3	the	the	DET
fcis-9761	100	4	proposed	propose	VERB
fcis-9761	100	5	network	network	NOUN
fcis-9761	100	6	consists	consist	VERB
fcis-9761	100	7	of	of	ADP
fcis-9761	100	8	a	a	DET
fcis-9761	100	9	haze	haze	NOUN
fcis-9761	100	10	removal	removal	NOUN
fcis-9761	100	11	sub	sub	NOUN
fcis-9761	100	12	-	-	NOUN
fcis-9761	100	13	network	network	NOUN
fcis-9761	100	14	and	and	CCONJ
fcis-9761	100	15	an	an	DET
fcis-9761	100	16	image	image	NOUN
fcis-9761	100	17	enhancement	enhancement	NOUN
fcis-9761	100	18	sub	sub	NOUN
fcis-9761	100	19	-	-	NOUN
fcis-9761	100	20	network	network	NOUN
fcis-9761	100	21	.	.	PUNCT
fcis-9761	101	1	the	the	DET
fcis-9761	101	2	tied	tie	VERB
fcis-9761	101	3	block	block	NOUN
fcis-9761	101	4	convolution	convolution	NOUN
fcis-9761	101	5	(	(	PUNCT
fcis-9761	101	6	tbc	tbc	NOUN
fcis-9761	101	7	)	)	PUNCT
fcis-9761	101	8	is	be	AUX
fcis-9761	101	9	employed	employ	VERB
fcis-9761	101	10	with	with	ADP
fcis-9761	101	11	parameter	parameter	NOUN
fcis-9761	101	12	sharing	sharing	NOUN
fcis-9761	101	13	to	to	PART
fcis-9761	101	14	reduce	reduce	VERB
fcis-9761	101	15	computational	computational	ADJ
fcis-9761	101	16	and	and	CCONJ
fcis-9761	101	17	parameter	parameter	NOUN
fcis-9761	101	18	complexity	complexity	NOUN
fcis-9761	101	19	.	.	PUNCT
fcis-9761	102	1	finally	finally	ADV
fcis-9761	102	2	,	,	PUNCT
fcis-9761	102	3	through	through	ADP
fcis-9761	102	4	correlation	correlation	NOUN
fcis-9761	102	5	learning	learning	NOUN
fcis-9761	102	6	,	,	PUNCT
fcis-9761	102	7	the	the	DET
fcis-9761	102	8	different	different	ADJ
fcis-9761	102	9	features	feature	NOUN
fcis-9761	102	10	of	of	ADP
fcis-9761	102	11	these	these	DET
fcis-9761	102	12	subnetworks	subnetwork	NOUN
fcis-9761	102	13	are	be	AUX
fcis-9761	102	14	mapped	map	VERB
fcis-9761	102	15	.	.	PUNCT
fcis-9761	103	1	the	the	DET
fcis-9761	103	2	proposed	propose	VERB
fcis-9761	103	3	model	model	NOUN
fcis-9761	103	4	demonstrates	demonstrate	VERB
fcis-9761	103	5	qualitative	qualitative	ADJ
fcis-9761	103	6	and	and	CCONJ
fcis-9761	103	7	quantitative	quantitative	ADJ
fcis-9761	103	8	advantages	advantage	NOUN
fcis-9761	103	9	,	,	PUNCT
fcis-9761	103	10	yielding	yield	VERB
fcis-9761	103	11	superior	superior	ADJ
fcis-9761	103	12	dehazing	dehazing	NOUN
fcis-9761	103	13	results	result	NOUN
fcis-9761	103	14	.	.	PUNCT
fcis-9761	104	1	moreover	moreover	ADV
fcis-9761	104	2	,	,	PUNCT
fcis-9761	104	3	it	it	PRON
fcis-9761	104	4	has	have	VERB
fcis-9761	104	5	low	low	ADJ
fcis-9761	104	6	computational	computational	ADJ
fcis-9761	104	7	and	and	CCONJ
fcis-9761	104	8	parameter	parameter	NOUN
fcis-9761	104	9	requirements	requirement	NOUN
fcis-9761	104	10	,	,	PUNCT
fcis-9761	104	11	saving	save	VERB
fcis-9761	104	12	computational	computational	ADJ
fcis-9761	104	13	resources	resource	NOUN
fcis-9761	104	14	,	,	PUNCT
fcis-9761	104	15	and	and	CCONJ
fcis-9761	104	16	thus	thus	ADV
fcis-9761	104	17	holds	hold	VERB
fcis-9761	104	18	significant	significant	ADJ
fcis-9761	104	19	practical	practical	ADJ
fcis-9761	104	20	value	value	NOUN
fcis-9761	104	21	for	for	ADP
fcis-9761	104	22	real	real	ADJ
fcis-9761	104	23	-	-	PUNCT
fcis-9761	104	24	world	world	NOUN
fcis-9761	104	25	image	image	NOUN
fcis-9761	104	26	dehazing	dehazing	NOUN
fcis-9761	104	27	.	.	PUNCT
fcis-9761	105	1	future	future	ADJ
fcis-9761	105	2	applications	application	NOUN
fcis-9761	105	3	and	and	CCONJ
fcis-9761	105	4	improvements	improvement	NOUN
fcis-9761	105	5	can	can	AUX
fcis-9761	105	6	be	be	AUX
fcis-9761	105	7	explored	explore	VERB
fcis-9761	105	8	in	in	ADP
fcis-9761	105	9	the	the	DET
fcis-9761	105	10	domain	domain	NOUN
fcis-9761	105	11	of	of	ADP
fcis-9761	105	12	video	video	NOUN
fcis-9761	105	13	dehazing	dehazing	NOUN
fcis-9761	105	14	.	.	PUNCT
fcis-9761	106	1	additionally	additionally	ADV
fcis-9761	106	2	,	,	PUNCT
fcis-9761	106	3	this	this	DET
fcis-9761	106	4	paper	paper	NOUN
fcis-9761	106	5	does	do	AUX
fcis-9761	106	6	not	not	PART
fcis-9761	106	7	cover	cover	VERB
fcis-9761	106	8	the	the	DET
fcis-9761	106	9	scenario	scenario	NOUN
fcis-9761	106	10	of	of	ADP
fcis-9761	106	11	nighttime	nighttime	ADJ
fcis-9761	106	12	dehazing	dehazing	NOUN
fcis-9761	106	13	,	,	PUNCT
fcis-9761	106	14	which	which	PRON
fcis-9761	106	15	is	be	AUX
fcis-9761	106	16	another	another	DET
fcis-9761	106	17	area	area	NOUN
fcis-9761	106	18	worthy	worthy	ADJ
fcis-9761	106	19	of	of	ADP
fcis-9761	106	20	investigation	investigation	NOUN
fcis-9761	106	21	.	.	PUNCT
fcis-9761	107	1	references	reference	NOUN
fcis-9761	107	2	[	[	X
fcis-9761	107	3	1	1	NUM
fcis-9761	107	4	]	]	PUNCT
fcis-9761	107	5	w.	w.	PROPN
fcis-9761	107	6	e.	e.	PROPN
fcis-9761	107	7	k.	k.	PROPN
fcis-9761	107	8	middleton	middleton	PROPN
fcis-9761	107	9	.	.	PUNCT
fcis-9761	108	1	vision	vision	PROPN
fcis-9761	108	2	through	through	ADP
fcis-9761	108	3	the	the	DET
fcis-9761	108	4	atmosphere	atmosphere	NOUN
fcis-9761	108	5	.	.	PUNCT
fcis-9761	109	1	university	university	NOUN
fcis-9761	109	2	of	of	ADP
fcis-9761	109	3	toronto	toronto	PROPN
fcis-9761	109	4	press	press	PROPN
fcis-9761	109	5	,	,	PUNCT
fcis-9761	109	6	1952	1952	NUM
fcis-9761	109	7	.	.	PUNCT
fcis-9761	110	1	[	[	X
fcis-9761	110	2	2	2	NUM
fcis-9761	110	3	]	]	X
fcis-9761	110	4	turgay	turgay	NOUN
fcis-9761	110	5	celik	celik	NOUN
fcis-9761	110	6	.	.	PUNCT
fcis-9761	111	1	spatial	spatial	ADJ
fcis-9761	111	2	entropy	entropy	NOUN
fcis-9761	111	3	-	-	PUNCT
fcis-9761	111	4	based	base	VERB
fcis-9761	111	5	global	global	ADJ
fcis-9761	111	6	and	and	CCONJ
fcis-9761	111	7	local	local	ADJ
fcis-9761	111	8	image	image	NOUN
fcis-9761	111	9	contrast	contrast	NOUN
fcis-9761	111	10	enhancement[j	enhancement[j	ADV
fcis-9761	111	11	]	]	PUNCT
fcis-9761	111	12	.	.	PUNCT
fcis-9761	112	1	ieee	ieee	NOUN
fcis-9761	112	2	transactions	transaction	NOUN
fcis-9761	112	3	on	on	ADP
fcis-9761	112	4	image	image	NOUN
fcis-9761	112	5	processing	processing	NOUN
fcis-9761	112	6	,	,	PUNCT
fcis-9761	112	7	2014	2014	NUM
fcis-9761	112	8	,	,	PUNCT
fcis-9761	112	9	23(12	23(12	NUM
fcis-9761	112	10	):	):	PUNCT
fcis-9761	112	11	5298	5298	NUM
fcis-9761	112	12	-	-	SYM
fcis-9761	112	13	5308	5308	NUM
fcis-9761	112	14	.	.	PUNCT
fcis-9761	113	1	[	[	X
fcis-9761	113	2	3	3	NUM
fcis-9761	113	3	]	]	X
fcis-9761	113	4	stark	stark	PROPN
fcis-9761	113	5	j	j	PROPN
fcis-9761	113	6	a.	a.	NOUN
fcis-9761	113	7	adaptive	adaptive	PROPN
fcis-9761	113	8	image	image	NOUN
fcis-9761	113	9	contrast	contrast	NOUN
fcis-9761	113	10	enhancement	enhancement	NOUN
fcis-9761	113	11	using	use	VERB
fcis-9761	113	12	generalizations	generalization	NOUN
fcis-9761	113	13	of	of	ADP
fcis-9761	113	14	histogram	histogram	NOUN
fcis-9761	113	15	equalization[j	equalization[j	PROPN
fcis-9761	113	16	]	]	PUNCT
fcis-9761	113	17	.	.	PUNCT
fcis-9761	114	1	ieee	ieee	NOUN
fcis-9761	114	2	transactions	transaction	NOUN
fcis-9761	114	3	on	on	ADP
fcis-9761	114	4	image	image	NOUN
fcis-9761	114	5	processing,2000,9(5):889	processing,2000,9(5):889	NOUN
fcis-9761	114	6	-	-	PUNCT
fcis-9761	114	7	896	896	NUM
fcis-9761	114	8	.	.	PUNCT
fcis-9761	115	1	[	[	X
fcis-9761	115	2	4	4	X
fcis-9761	115	3	]	]	X
fcis-9761	115	4	kim	kim	PROPN
fcis-9761	115	5	j	j	PROPN
fcis-9761	115	6	y	y	PROPN
fcis-9761	115	7	,	,	PUNCT
fcis-9761	115	8	kim	kim	PROPN
fcis-9761	115	9	l	l	PROPN
fcis-9761	115	10	s	s	PROPN
fcis-9761	115	11	,	,	PUNCT
fcis-9761	115	12	hwang	hwang	PROPN
fcis-9761	115	13	s	s	PROPN
fcis-9761	115	14	h.	h.	NOUN
fcis-9761	115	15	an	an	DET
fcis-9761	115	16	advanced	advanced	ADJ
fcis-9761	115	17	contrast	contrast	NOUN
fcis-9761	115	18	enhancement	enhancement	NOUN
fcis-9761	115	19	using	use	VERB
fcis-9761	115	20	partially	partially	ADV
fcis-9761	115	21	overlapped	overlap	VERB
fcis-9761	115	22	sub	sub	ADJ
fcis-9761	115	23	-	-	ADJ
fcis-9761	115	24	block	block	ADJ
fcis-9761	115	25	histogram	histogram	NOUN
fcis-9761	115	26	equalization	equalization	NOUN
fcis-9761	116	1	[	[	X
fcis-9761	116	2	j	j	X
fcis-9761	116	3	]	]	X
fcis-9761	116	4	.	.	PUNCT
fcis-9761	117	1	ieee	ieee	NOUN
fcis-9761	117	2	transactions	transaction	NOUN
fcis-9761	117	3	on	on	ADP
fcis-9761	117	4	circuits	circuit	NOUN
fcis-9761	117	5	and	and	CCONJ
fcis-9761	117	6	systems	system	NOUN
fcis-9761	117	7	for	for	ADP
fcis-9761	117	8	video	video	NOUN
fcis-9761	117	9	technology,2001,11(4):475	technology,2001,11(4):475	NOUN
fcis-9761	117	10	-	-	PUNCT
fcis-9761	117	11	484	484	NUM
fcis-9761	117	12	.	.	PUNCT
fcis-9761	118	1	[	[	X
fcis-9761	118	2	5	5	X
fcis-9761	118	3	]	]	PUNCT
fcis-9761	118	4	russo	russo	PROPN
fcis-9761	118	5	f.	f.	PROPN
fcis-9761	118	6	an	an	DET
fcis-9761	118	7	image	image	NOUN
fcis-9761	118	8	enhancement	enhancement	NOUN
fcis-9761	118	9	technique	technique	NOUN
fcis-9761	118	10	combining	combine	VERB
fcis-9761	118	11	sharpening	sharpening	NOUN
fcis-9761	118	12	and	and	CCONJ
fcis-9761	118	13	noise	noise	NOUN
fcis-9761	118	14	reduction	reduction	NOUN
fcis-9761	118	15	.	.	PUNCT
fcis-9761	119	1	ieee	ieee	NOUN
fcis-9761	119	2	transactions	transaction	NOUN
fcis-9761	119	3	on	on	ADP
fcis-9761	119	4	instrumentation	instrumentation	NOUN
fcis-9761	119	5	and	and	CCONJ
fcis-9761	119	6	measurement	measurement	NOUN
fcis-9761	119	7	,	,	PUNCT
fcis-9761	119	8	2002	2002	NUM
fcis-9761	119	9	,	,	PUNCT
fcis-9761	119	10	51(4	51(4	NUM
fcis-9761	119	11	):	):	PUNCT
fcis-9761	119	12	824−828	824−828	X
fcis-9761	119	13	.	.	PUNCT
fcis-9761	120	1	[	[	X
fcis-9761	120	2	6	6	NUM
fcis-9761	120	3	]	]	X
fcis-9761	120	4	dippel	dippel	NOUN
fcis-9761	120	5	s	s	PROPN
fcis-9761	120	6	,	,	PUNCT
fcis-9761	120	7	stahl	stahl	PROPN
fcis-9761	120	8	m	m	PROPN
fcis-9761	120	9	,	,	PUNCT
fcis-9761	120	10	wiemker	wiemker	NOUN
fcis-9761	120	11	r	r	NOUN
fcis-9761	120	12	,	,	PUNCT
fcis-9761	120	13	blaffert	blaffert	ADJ
fcis-9761	120	14	t.	t.	PROPN
fcis-9761	120	15	multiscale	multiscale	PROPN
fcis-9761	120	16	contrast	contrast	NOUN
fcis-9761	120	17	enhancement	enhancement	NOUN
fcis-9761	120	18	for	for	ADP
fcis-9761	120	19	radiographies	radiography	NOUN
fcis-9761	120	20	:	:	PUNCT
fcis-9761	120	21	laplacian	laplacian	ADJ
fcis-9761	120	22	pyramid	pyramid	NOUN
fcis-9761	120	23	versus	versus	ADP
fcis-9761	120	24	fast	fast	ADJ
fcis-9761	120	25	wavelet	wavelet	NOUN
fcis-9761	120	26	transform	transform	NOUN
fcis-9761	120	27	.	.	PUNCT
fcis-9761	121	1	ieee	ieee	NOUN
fcis-9761	121	2	transactions	transaction	NOUN
fcis-9761	121	3	on	on	ADP
fcis-9761	121	4	medical	medical	ADJ
fcis-9761	121	5	imaging	imaging	NOUN
fcis-9761	121	6	,	,	PUNCT
fcis-9761	121	7	2002	2002	NUM
fcis-9761	121	8	,	,	PUNCT
fcis-9761	121	9	21(4	21(4	NUM
fcis-9761	121	10	):	):	PUNCT
fcis-9761	121	11	343−353	343−353	PROPN
fcis-9761	121	12	.	.	NOUN
fcis-9761	121	13	30	30	NUM
fcis-9761	121	14	[	[	SYM
fcis-9761	121	15	7	7	NUM
fcis-9761	121	16	]	]	X
fcis-9761	121	17	land	land	NOUN
fcis-9761	121	18	e	e	NOUN
fcis-9761	121	19	h	h	NOUN
fcis-9761	121	20	,	,	PUNCT
fcis-9761	121	21	mccann	mccann	PROPN
fcis-9761	121	22	j	j	PROPN
fcis-9761	121	23	j.	j.	PROPN
fcis-9761	121	24	lightness	lightness	PROPN
fcis-9761	121	25	and	and	CCONJ
fcis-9761	121	26	retinex	retinex	ADJ
fcis-9761	121	27	theory[j	theory[j	PROPN
fcis-9761	121	28	]	]	PUNCT
fcis-9761	121	29	.	.	PUNCT
fcis-9761	122	1	journal	journal	PROPN
fcis-9761	122	2	of	of	ADP
fcis-9761	122	3	the	the	DET
fcis-9761	122	4	optical	optical	ADJ
fcis-9761	122	5	society	society	NOUN
fcis-9761	122	6	of	of	ADP
fcis-9761	122	7	america	america	PROPN
fcis-9761	122	8	,	,	PUNCT
fcis-9761	122	9	1971,61(1):1	1971,61(1):1	PROPN
fcis-9761	122	10	-	-	SYM
fcis-9761	122	11	11	11	NUM
fcis-9761	122	12	.	.	PUNCT
fcis-9761	123	1	[	[	X
fcis-9761	123	2	8	8	NUM
fcis-9761	123	3	]	]	PUNCT
fcis-9761	123	4	he	he	PRON
fcis-9761	123	5	k	k	PROPN
fcis-9761	123	6	m	m	PROPN
fcis-9761	123	7	,	,	PUNCT
fcis-9761	123	8	sun	sun	PROPN
fcis-9761	123	9	j	j	PROPN
fcis-9761	123	10	,	,	PUNCT
fcis-9761	123	11	tang	tang	PROPN
fcis-9761	123	12	x	x	SYM
fcis-9761	123	13	o.	o.	PROPN
fcis-9761	123	14	single	single	ADJ
fcis-9761	123	15	image	image	NOUN
fcis-9761	123	16	haze	haze	NOUN
fcis-9761	123	17	removal	removal	NOUN
fcis-9761	123	18	using	use	VERB
fcis-9761	123	19	dark	dark	ADJ
fcis-9761	123	20	channel	channel	NOUN
fcis-9761	123	21	prior[j	prior[j	NOUN
fcis-9761	123	22	]	]	PUNCT
fcis-9761	123	23	.	.	PUNCT
fcis-9761	124	1	ieee	ieee	NOUN
fcis-9761	124	2	transactions	transaction	NOUN
fcis-9761	124	3	on	on	ADP
fcis-9761	124	4	pattern	pattern	NOUN
fcis-9761	124	5	analysis	analysis	NOUN
fcis-9761	124	6	and	and	CCONJ
fcis-9761	124	7	machine	machine	NOUN
fcis-9761	124	8	intelligence	intelligence	NOUN
fcis-9761	124	9	,	,	PUNCT
fcis-9761	124	10	2011,33(12	2011,33(12	NUM
fcis-9761	124	11	):	):	PUNCT
fcis-9761	124	12	2341	2341	NUM
fcis-9761	124	13	-	-	SYM
fcis-9761	124	14	2353	2353	NUM
fcis-9761	124	15	.	.	PUNCT
fcis-9761	125	1	[	[	X
fcis-9761	125	2	9	9	NUM
fcis-9761	125	3	]	]	X
fcis-9761	125	4	tan	tan	NOUN
fcis-9761	125	5	r	r	NOUN
fcis-9761	125	6	t.	t.	NOUN
fcis-9761	125	7	visibility	visibility	NOUN
fcis-9761	125	8	in	in	ADP
fcis-9761	125	9	bad	bad	ADJ
fcis-9761	125	10	weather	weather	NOUN
fcis-9761	125	11	from	from	ADP
fcis-9761	125	12	a	a	DET
fcis-9761	125	13	single	single	ADJ
fcis-9761	125	14	image[c	image[c	NOUN
fcis-9761	125	15	]	]	PUNCT
fcis-9761	125	16	.	.	PUNCT
fcis-9761	126	1	ieee	ieee	PROPN
fcis-9761	126	2	conference	conference	PROPN
fcis-9761	126	3	on	on	ADP
fcis-9761	126	4	computer	computer	NOUN
fcis-9761	126	5	vision	vision	NOUN
fcis-9761	126	6	and	and	CCONJ
fcis-9761	126	7	pattern	pattern	NOUN
fcis-9761	126	8	recognition	recognition	NOUN
fcis-9761	126	9	,	,	PUNCT
fcis-9761	126	10	anchorage	anchorage	PROPN
fcis-9761	126	11	,	,	PUNCT
fcis-9761	126	12	usa	usa	PROPN
fcis-9761	126	13	,	,	PUNCT
fcis-9761	126	14	2008	2008	NUM
fcis-9761	126	15	:	:	PUNCT
fcis-9761	126	16	2347	2347	NUM
fcis-9761	126	17	-	-	SYM
fcis-9761	126	18	2354	2354	NUM
fcis-9761	126	19	.	.	PUNCT
fcis-9761	127	1	[	[	X
fcis-9761	127	2	10	10	NUM
fcis-9761	127	3	]	]	X
fcis-9761	127	4	cai	cai	PROPN
fcis-9761	127	5	b	b	PROPN
fcis-9761	127	6	l	l	PROPN
fcis-9761	127	7	,	,	PUNCT
fcis-9761	127	8	xu	xu	PROPN
fcis-9761	127	9	x	x	PROPN
fcis-9761	127	10	m	m	PROPN
fcis-9761	127	11	,	,	PUNCT
fcis-9761	127	12	jia	jia	PROPN
fcis-9761	127	13	k	k	PROPN
fcis-9761	127	14	,	,	PUNCT
fcis-9761	127	15	et	et	PROPN
fcis-9761	127	16	al	al	PROPN
fcis-9761	127	17	.	.	PUNCT
fcis-9761	127	18	dehazenet	dehazenet	PROPN
fcis-9761	127	19	:	:	PUNCT
fcis-9761	127	20	an	an	DET
fcis-9761	127	21	endto	endto	NOUN
fcis-9761	127	22	-	-	PUNCT
fcis-9761	127	23	end	end	NOUN
fcis-9761	127	24	system	system	NOUN
fcis-9761	127	25	for	for	ADP
fcis-9761	127	26	single	single	ADJ
fcis-9761	127	27	image	image	NOUN
fcis-9761	127	28	haze	haze	NOUN
fcis-9761	127	29	removal[j	removal[j	NOUN
fcis-9761	127	30	]	]	PUNCT
fcis-9761	127	31	.	.	PUNCT
fcis-9761	128	1	ieee	ieee	NOUN
fcis-9761	128	2	transactions	transaction	NOUN
fcis-9761	128	3	on	on	ADP
fcis-9761	128	4	image	image	NOUN
fcis-9761	128	5	processing	processing	NOUN
fcis-9761	128	6	,	,	PUNCT
fcis-9761	128	7	2016	2016	NUM
fcis-9761	128	8	,	,	PUNCT
fcis-9761	128	9	25(11):5187	25(11):5187	NUM
fcis-9761	128	10	-	-	SYM
fcis-9761	128	11	5198	5198	NUM
fcis-9761	128	12	.	.	PUNCT
fcis-9761	129	1	[	[	X
fcis-9761	129	2	11	11	NUM
fcis-9761	129	3	]	]	X
fcis-9761	129	4	li	li	PROPN
fcis-9761	129	5	b	b	PROPN
fcis-9761	129	6	y	y	PROPN
fcis-9761	129	7	,	,	PUNCT
fcis-9761	129	8	peng	peng	PROPN
fcis-9761	129	9	x	x	PROPN
fcis-9761	129	10	l	l	PROPN
fcis-9761	129	11	,	,	PUNCT
fcis-9761	129	12	wang	wang	PROPN
fcis-9761	129	13	z	z	PROPN
fcis-9761	129	14	y	y	PROPN
fcis-9761	129	15	,	,	PUNCT
fcis-9761	129	16	et	et	PROPN
fcis-9761	129	17	al	al	PROPN
fcis-9761	129	18	.	.	PROPN
fcis-9761	129	19	aod	aod	PROPN
fcis-9761	129	20	-	-	NOUN
fcis-9761	129	21	net	net	NOUN
fcis-9761	129	22	:	:	PUNCT
fcis-9761	129	23	all	all	PRON
fcis-9761	129	24	-	-	PUNCT
fcis-9761	129	25	in	in	ADP
fcis-9761	129	26	-	-	PUNCT
fcis-9761	129	27	one	one	NUM
fcis-9761	129	28	dehazing	dehaze	VERB
fcis-9761	129	29	network[c	network[c	NOUN
fcis-9761	129	30	]	]	PUNCT
fcis-9761	129	31	.	.	PUNCT
fcis-9761	130	1	ieee	ieee	PROPN
fcis-9761	130	2	international	international	PROPN
fcis-9761	130	3	conference	conference	NOUN
fcis-9761	130	4	on	on	ADP
fcis-9761	130	5	computer	computer	NOUN
fcis-9761	130	6	vision,2017:4770	vision,2017:4770	NOUN
fcis-9761	130	7	-	-	SYM
fcis-9761	130	8	4778	4778	NUM
fcis-9761	130	9	.	.	PUNCT
fcis-9761	131	1	[	[	X
fcis-9761	131	2	12	12	NUM
fcis-9761	131	3	]	]	X
fcis-9761	131	4	ren	ren	PROPN
fcis-9761	131	5	w	w	PROPN
fcis-9761	132	1	q	q	PROPN
fcis-9761	132	2	,	,	PUNCT
fcis-9761	132	3	liu	liu	PROPN
fcis-9761	132	4	s	s	PROPN
fcis-9761	132	5	,	,	PUNCT
fcis-9761	132	6	zhang	zhang	PROPN
fcis-9761	132	7	h	h	PROPN
fcis-9761	132	8	,	,	PUNCT
fcis-9761	132	9	et	et	PROPN
fcis-9761	132	10	al	al	PROPN
fcis-9761	132	11	.	.	PUNCT
fcis-9761	132	12	single	single	ADJ
fcis-9761	132	13	image	image	NOUN
fcis-9761	132	14	dehazing	dehazing	NOUN
fcis-9761	132	15	via	via	ADP
fcis-9761	132	16	multiscale	multiscale	ADJ
fcis-9761	132	17	convolutional	convolutional	ADJ
fcis-9761	132	18	neural	neural	NOUN
fcis-9761	132	19	networks[c	networks[c	PROPN
fcis-9761	132	20	]	]	PUNCT
fcis-9761	132	21	.	.	PUNCT
fcis-9761	133	1	european	european	ADJ
fcis-9761	133	2	conference	conference	PROPN
fcis-9761	133	3	on	on	ADP
fcis-9761	133	4	computer	computer	NOUN
fcis-9761	133	5	vision,2016:154	vision,2016:154	NOUN
fcis-9761	133	6	-	-	SYM
fcis-9761	133	7	169	169	NUM
fcis-9761	133	8	.	.	PUNCT
fcis-9761	134	1	[	[	X
fcis-9761	134	2	13	13	NUM
fcis-9761	134	3	]	]	X
fcis-9761	134	4	chen	chen	PROPN
fcis-9761	134	5	d	d	PROPN
fcis-9761	134	6	,	,	PUNCT
fcis-9761	134	7	he	he	PRON
fcis-9761	134	8	m	m	PROPN
fcis-9761	134	9	,	,	PUNCT
fcis-9761	134	10	fan	fan	PROPN
fcis-9761	134	11	q	q	PROPN
fcis-9761	134	12	,	,	PUNCT
fcis-9761	134	13	et	et	PROPN
fcis-9761	134	14	al	al	PROPN
fcis-9761	134	15	.	.	PROPN
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fcis-9761	134	17	context	context	NOUN
fcis-9761	134	18	aggregation	aggregation	NOUN
fcis-9761	134	19	network	network	NOUN
fcis-9761	134	20	for	for	ADP
fcis-9761	134	21	image	image	NOUN
fcis-9761	134	22	dehazing	dehazing	NOUN
fcis-9761	134	23	and	and	CCONJ
fcis-9761	134	24	deraining[c	deraining[c	NOUN
fcis-9761	134	25	]	]	PUNCT
fcis-9761	134	26	.	.	PUNCT
fcis-9761	135	1	proceedings	proceeding	NOUN
fcis-9761	135	2	of	of	ADP
fcis-9761	135	3	the	the	DET
fcis-9761	135	4	2019	2019	NUM
fcis-9761	135	5	ieee	ieee	NOUN
fcis-9761	135	6	winter	winter	NOUN
fcis-9761	135	7	conference	conference	NOUN
fcis-9761	135	8	on	on	ADP
fcis-9761	135	9	applications	application	NOUN
fcis-9761	135	10	of	of	ADP
fcis-9761	135	11	computer	computer	NOUN
fcis-9761	135	12	vision	vision	NOUN
fcis-9761	135	13	.	.	PUNCT
fcis-9761	136	1	2019	2019	NUM
fcis-9761	136	2	:	:	PUNCT
fcis-9761	136	3	1375	1375	NUM
fcis-9761	136	4	-	-	SYM
fcis-9761	136	5	1383	1383	NUM
fcis-9761	136	6	.	.	PUNCT
fcis-9761	137	1	[	[	X
fcis-9761	137	2	14	14	NUM
fcis-9761	137	3	]	]	X
fcis-9761	137	4	qin	qin	PROPN
fcis-9761	137	5	x	x	PROPN
fcis-9761	137	6	,	,	PUNCT
fcis-9761	137	7	wang	wang	PROPN
fcis-9761	137	8	z	z	PROPN
fcis-9761	137	9	,	,	PUNCT
fcis-9761	137	10	bai	bai	PROPN
fcis-9761	137	11	y	y	PROPN
fcis-9761	137	12	,	,	PUNCT
fcis-9761	137	13	et	et	PROPN
fcis-9761	137	14	al	al	PROPN
fcis-9761	137	15	.	.	PUNCT
fcis-9761	138	1	ffa	ffa	PROPN
fcis-9761	138	2	-	-	PUNCT
fcis-9761	138	3	net	net	NOUN
fcis-9761	138	4	:	:	PUNCT
fcis-9761	138	5	feature	feature	NOUN
fcis-9761	138	6	fusion	fusion	NOUN
fcis-9761	138	7	attention	attention	NOUN
fcis-9761	138	8	network	network	NOUN
fcis-9761	138	9	for	for	ADP
fcis-9761	138	10	single	single	ADJ
fcis-9761	138	11	image	image	NOUN
fcis-9761	138	12	dehazing[c	dehazing[c	NOUN
fcis-9761	138	13	]	]	PUNCT
fcis-9761	138	14	.	.	PUNCT
fcis-9761	139	1	proceedings	proceeding	NOUN
fcis-9761	139	2	of	of	ADP
fcis-9761	139	3	the	the	DET
fcis-9761	139	4	aaai	aaai	PROPN
fcis-9761	139	5	conference	conference	NOUN
fcis-9761	139	6	on	on	ADP
fcis-9761	139	7	artificial	artificial	ADJ
fcis-9761	139	8	intelligence	intelligence	NOUN
fcis-9761	139	9	.	.	PUNCT
fcis-9761	140	1	2020	2020	NUM
fcis-9761	140	2	,	,	PUNCT
fcis-9761	140	3	34(07	34(07	NUM
fcis-9761	140	4	):	):	PUNCT
fcis-9761	140	5	11908	11908	NUM
fcis-9761	140	6	-	-	SYM
fcis-9761	140	7	11915	11915	NUM
fcis-9761	140	8	.	.	PUNCT
fcis-9761	141	1	[	[	X
fcis-9761	141	2	15	15	NUM
fcis-9761	141	3	]	]	X
fcis-9761	141	4	lai	lai	PROPN
fcis-9761	141	5	,	,	PUNCT
fcis-9761	141	6	wei	wei	PROPN
fcis-9761	141	7	sheng	sheng	PROPN
fcis-9761	141	8	,	,	PUNCT
fcis-9761	141	9	et	et	PROPN
fcis-9761	141	10	al	al	PROPN
fcis-9761	141	11	.	.	PUNCT
fcis-9761	142	1	deep	deep	ADJ
fcis-9761	142	2	laplacian	laplacian	ADJ
fcis-9761	142	3	pyramid	pyramid	NOUN
fcis-9761	142	4	networks	network	NOUN
fcis-9761	142	5	for	for	ADP
fcis-9761	142	6	fast	fast	ADJ
fcis-9761	142	7	and	and	CCONJ
fcis-9761	142	8	accurate	accurate	ADJ
fcis-9761	142	9	super	super	NOUN
fcis-9761	142	10	-	-	NOUN
fcis-9761	142	11	resolution	resolution	NOUN
fcis-9761	142	12	[	[	X
fcis-9761	142	13	c	c	X
fcis-9761	142	14	]	]	PUNCT
fcis-9761	142	15	.	.	PUNCT
fcis-9761	143	1	ieee	ieee	PROPN
fcis-9761	143	2	conference	conference	PROPN
fcis-9761	143	3	on	on	ADP
fcis-9761	143	4	computer	computer	NOUN
fcis-9761	143	5	vision	vision	NOUN
fcis-9761	143	6	and	and	CCONJ
fcis-9761	143	7	pattern	pattern	NOUN
fcis-9761	143	8	recognition	recognition	NOUN
fcis-9761	143	9	.	.	PUNCT
fcis-9761	144	1	ieee	ieee	NOUN
fcis-9761	144	2	computer	computer	NOUN
fcis-9761	144	3	society	society	NOUN
fcis-9761	144	4	,	,	PUNCT
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fcis-9761	144	6	-	-	SYM
fcis-9761	144	7	5843	5843	NUM
fcis-9761	144	8	.	.	PUNCT
fcis-9761	145	1	[	[	X
fcis-9761	145	2	16	16	NUM
fcis-9761	145	3	]	]	X
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fcis-9761	145	5	z	z	PROPN
fcis-9761	145	6	,	,	PUNCT
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fcis-9761	145	8	a	a	DET
fcis-9761	145	9	c	c	NOUN
fcis-9761	145	10	,	,	PUNCT
fcis-9761	145	11	sheikh	sheikh	NOUN
fcis-9761	145	12	h	h	NOUN
fcis-9761	145	13	r	r	NOUN
fcis-9761	145	14	,	,	PUNCT
fcis-9761	145	15	et	et	NOUN
fcis-9761	145	16	al.image	al.image	VERB
fcis-9761	145	17	quality	quality	NOUN
fcis-9761	145	18	assessment	assessment	NOUN
fcis-9761	145	19	:	:	PUNCT
fcis-9761	145	20	from	from	ADP
fcis-9761	145	21	error	error	NOUN
fcis-9761	145	22	visibility	visibility	NOUN
fcis-9761	145	23	to	to	ADP
fcis-9761	145	24	structural	structural	ADJ
fcis-9761	145	25	similarity	similarity	NOUN
fcis-9761	146	1	[	[	X
fcis-9761	146	2	j	j	X
fcis-9761	146	3	]	]	X
fcis-9761	146	4	.	.	PUNCT
fcis-9761	147	1	ieee	ieee	PROPN
fcis-9761	147	2	trans	trans	PROPN
fcis-9761	147	3	image	image	NOUN
fcis-9761	147	4	process	process	NOUN
fcis-9761	147	5	,	,	PUNCT
fcis-9761	147	6	2004	2004	NUM
fcis-9761	147	7	,	,	PUNCT
fcis-9761	147	8	13(4	13(4	NUM
fcis-9761	147	9	)	)	PUNCT
fcis-9761	147	10	.	.	PUNCT
fcis-9761	148	1	[	[	X
fcis-9761	148	2	17	17	NUM
fcis-9761	148	3	]	]	X
fcis-9761	148	4	li	li	PROPN
fcis-9761	148	5	b	b	PROPN
fcis-9761	148	6	,	,	PUNCT
fcis-9761	148	7	ren	ren	PROPN
fcis-9761	148	8	w	w	PROPN
fcis-9761	148	9	,	,	PUNCT
fcis-9761	148	10	fu	fu	NOUN
fcis-9761	148	11	d	d	PROPN
fcis-9761	148	12	,	,	PUNCT
fcis-9761	148	13	et	et	PROPN
fcis-9761	148	14	al	al	PROPN
fcis-9761	148	15	.	.	PUNCT
fcis-9761	148	16	benchmarking	benchmarke	VERB
fcis-9761	148	17	single	single	ADJ
fcis-9761	148	18	-	-	PUNCT
fcis-9761	148	19	image	image	NOUN
fcis-9761	148	20	dehazing	dehazing	NOUN
fcis-9761	148	21	and	and	CCONJ
fcis-9761	148	22	beyond[j	beyond[j	NOUN
fcis-9761	148	23	]	]	PUNCT
fcis-9761	148	24	.	.	PUNCT
fcis-9761	149	1	ieee	ieee	NOUN
fcis-9761	149	2	transactions	transaction	NOUN
fcis-9761	149	3	on	on	ADP
fcis-9761	149	4	image	image	NOUN
fcis-9761	149	5	processing	processing	NOUN
fcis-9761	149	6	,	,	PUNCT
fcis-9761	149	7	2018	2018	NUM
fcis-9761	149	8	,	,	PUNCT
fcis-9761	149	9	28	28	NUM
fcis-9761	149	10	(	(	PUNCT
fcis-9761	149	11	1	1	NUM
fcis-9761	149	12	):	):	PUNCT
fcis-9761	149	13	492	492	NUM
fcis-9761	149	14	-	-	SYM
fcis-9761	149	15	505	505	NUM
fcis-9761	149	16	.	.	PUNCT
fcis-9761	150	1	[	[	X
fcis-9761	150	2	18	18	NUM
fcis-9761	150	3	]	]	X
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fcis-9761	150	5	c	c	PROPN
fcis-9761	150	6	,	,	PUNCT
fcis-9761	150	7	ancuti	ancuti	ADP
fcis-9761	150	8	c	c	PROPN
fcis-9761	150	9	o	o	NOUN
fcis-9761	150	10	,	,	PUNCT
fcis-9761	150	11	timofte	timofte	PROPN
fcis-9761	150	12	r	r	NOUN
fcis-9761	150	13	,	,	PUNCT
fcis-9761	150	14	et	et	PROPN
fcis-9761	150	15	al	al	PROPN
fcis-9761	150	16	.	.	PUNCT
fcis-9761	151	1	i	i	PRON
fcis-9761	151	2	-	-	PUNCT
fcis-9761	151	3	haze	haze	VERB
fcis-9761	151	4	:	:	PUNCT
fcis-9761	151	5	a	a	DET
fcis-9761	151	6	dehazing	dehaze	VERB
fcis-9761	151	7	benchmark	benchmark	NOUN
fcis-9761	151	8	with	with	ADP
fcis-9761	151	9	real	real	ADJ
fcis-9761	151	10	hazy	hazy	ADJ
fcis-9761	151	11	and	and	CCONJ
fcis-9761	151	12	haze	haze	NOUN
fcis-9761	151	13	-	-	PUNCT
fcis-9761	151	14	free	free	ADJ
fcis-9761	151	15	indoor	indoor	ADJ
fcis-9761	151	16	images[c	images[c	PROPN
fcis-9761	151	17	]	]	PUNCT
fcis-9761	151	18	.	.	PUNCT
fcis-9761	152	1	proceedings	proceeding	NOUN
fcis-9761	152	2	of	of	ADP
fcis-9761	152	3	the	the	DET
fcis-9761	152	4	advanced	advanced	ADJ
fcis-9761	152	5	concepts	concept	NOUN
fcis-9761	152	6	for	for	ADP
fcis-9761	152	7	intelligent	intelligent	ADJ
fcis-9761	152	8	vision	vision	NOUN
fcis-9761	152	9	systems	system	NOUN
fcis-9761	152	10	.	.	PUNCT
fcis-9761	153	1	2018	2018	NUM
fcis-9761	153	2	:	:	PUNCT
fcis-9761	153	3	620	620	NUM
fcis-9761	153	4	-	-	SYM
fcis-9761	153	5	631	631	NUM
fcis-9761	153	6	.	.	PUNCT
fcis-9761	154	1	[	[	X
fcis-9761	154	2	19	19	NUM
fcis-9761	154	3	]	]	X
fcis-9761	154	4	ancuti	ancuti	ADV
fcis-9761	154	5	c	c	NOUN
fcis-9761	154	6	o	o	NOUN
fcis-9761	154	7	,	,	PUNCT
fcis-9761	154	8	ancuti	ancuti	ADP
fcis-9761	154	9	c	c	AUX
fcis-9761	154	10	,	,	PUNCT
fcis-9761	154	11	timofte	timofte	NOUN
fcis-9761	154	12	r	r	NOUN
fcis-9761	154	13	,	,	PUNCT
fcis-9761	154	14	et	et	PROPN
fcis-9761	154	15	al	al	PROPN
fcis-9761	154	16	.	.	PUNCT
fcis-9761	155	1	o	o	X
fcis-9761	155	2	-	-	PUNCT
fcis-9761	155	3	haze	haze	VERB
fcis-9761	155	4	:	:	PUNCT
fcis-9761	155	5	a	a	DET
fcis-9761	155	6	dehazing	dehaze	VERB
fcis-9761	155	7	benchmark	benchmark	NOUN
fcis-9761	155	8	with	with	ADP
fcis-9761	155	9	real	real	ADJ
fcis-9761	155	10	hazy	hazy	ADJ
fcis-9761	155	11	and	and	CCONJ
fcis-9761	155	12	haze	haze	NOUN
fcis-9761	155	13	-	-	PUNCT
fcis-9761	155	14	free	free	ADJ
fcis-9761	155	15	outdoor	outdoor	NOUN
fcis-9761	155	16	images[c	images[c	PROPN
fcis-9761	155	17	]	]	PUNCT
fcis-9761	155	18	.	.	PUNCT
fcis-9761	156	1	proceedings	proceeding	NOUN
fcis-9761	156	2	of	of	ADP
fcis-9761	156	3	the	the	DET
fcis-9761	156	4	ieee	ieee	NOUN
fcis-9761	156	5	conference	conference	NOUN
fcis-9761	156	6	on	on	ADP
fcis-9761	156	7	computer	computer	NOUN
fcis-9761	156	8	vision	vision	NOUN
fcis-9761	156	9	and	and	CCONJ
fcis-9761	156	10	pattern	pattern	NOUN
fcis-9761	156	11	recognition	recognition	NOUN
fcis-9761	156	12	workshops	workshop	NOUN
fcis-9761	156	13	.	.	PUNCT
fcis-9761	157	1	2018	2018	NUM
fcis-9761	157	2	:	:	PUNCT
fcis-9761	157	3	754	754	NUM
fcis-9761	157	4	-	-	SYM
fcis-9761	157	5	762	762	NUM
fcis-9761	157	6	.	.	PUNCT
fcis-9761	158	1	[	[	X
fcis-9761	158	2	20	20	NUM
fcis-9761	158	3	]	]	X
fcis-9761	158	4	ancuti	ancuti	ADV
fcis-9761	158	5	c	c	X
fcis-9761	158	6	o	o	NOUN
fcis-9761	158	7	,	,	PUNCT
fcis-9761	158	8	ancuti	ancuti	ADP
fcis-9761	158	9	c	c	AUX
fcis-9761	158	10	,	,	PUNCT
fcis-9761	158	11	timofte	timofte	PROPN
fcis-9761	158	12	r.	r.	PROPN
fcis-9761	158	13	nh	nh	PROPN
fcis-9761	158	14	-	-	PUNCT
fcis-9761	158	15	haze	haze	NOUN
fcis-9761	158	16	:	:	PUNCT
fcis-9761	158	17	an	an	DET
fcis-9761	158	18	image	image	NOUN
fcis-9761	158	19	dehazing	dehaze	VERB
fcis-9761	158	20	benchmark	benchmark	NOUN
fcis-9761	158	21	with	with	ADP
fcis-9761	158	22	non	non	ADJ
fcis-9761	158	23	-	-	ADJ
fcis-9761	158	24	homogeneous	homogeneous	ADJ
fcis-9761	158	25	hazy	hazy	ADJ
fcis-9761	158	26	and	and	CCONJ
fcis-9761	158	27	hazefree	hazefree	NOUN
fcis-9761	158	28	images[c	images[c	PROPN
fcis-9761	158	29	]	]	PUNCT
fcis-9761	158	30	.	.	PUNCT
fcis-9761	159	1	proceedings	proceeding	NOUN
fcis-9761	159	2	of	of	ADP
fcis-9761	159	3	the	the	DET
fcis-9761	159	4	ieee	ieee	NOUN
fcis-9761	159	5	/	/	SYM
fcis-9761	159	6	cvf	cvf	NOUN
fcis-9761	159	7	conference	conference	NOUN
fcis-9761	159	8	on	on	ADP
fcis-9761	159	9	computer	computer	NOUN
fcis-9761	159	10	vision	vision	NOUN
fcis-9761	159	11	and	and	CCONJ
fcis-9761	159	12	pattern	pattern	NOUN
fcis-9761	159	13	recognition	recognition	NOUN
fcis-9761	159	14	workshops	workshop	NOUN
fcis-9761	159	15	.	.	PUNCT
fcis-9761	160	1	2020	2020	NUM
fcis-9761	160	2	:	:	PUNCT
fcis-9761	160	3	444445	444445	NUM
fcis-9761	160	4	.	.	PUNCT
fcis-9761	161	1	[	[	X
fcis-9761	161	2	21	21	NUM
fcis-9761	161	3	]	]	X
fcis-9761	161	4	li	li	PROPN
fcis-9761	161	5	l	l	PROPN
fcis-9761	161	6	,	,	PUNCT
fcis-9761	161	7	zhou	zhou	PROPN
fcis-9761	161	8	y	y	PROPN
fcis-9761	161	9	,	,	PUNCT
fcis-9761	161	10	wu	wu	PROPN
fcis-9761	161	11	j	j	PROPN
fcis-9761	161	12	,	,	PUNCT
fcis-9761	161	13	et	et	PROPN
fcis-9761	161	14	al	al	PROPN
fcis-9761	161	15	.	.	PUNCT
fcis-9761	161	16	color	color	NOUN
fcis-9761	161	17	-	-	PUNCT
fcis-9761	161	18	enriched	enrich	VERB
fcis-9761	161	19	gradient	gradient	ADJ
fcis-9761	161	20	similarity	similarity	NOUN
fcis-9761	161	21	for	for	ADP
fcis-9761	161	22	retouched	retouched	ADJ
fcis-9761	161	23	image	image	NOUN
fcis-9761	161	24	quality	quality	NOUN
fcis-9761	161	25	evaluation[j	evaluation[j	PROPN
fcis-9761	161	26	]	]	PUNCT
fcis-9761	161	27	.	.	PUNCT
fcis-9761	162	1	ieice	ieice	NOUN
fcis-9761	162	2	transactions	transaction	NOUN
fcis-9761	162	3	on	on	ADP
fcis-9761	162	4	information	information	NOUN
fcis-9761	162	5	and	and	CCONJ
fcis-9761	162	6	systems	system	NOUN
fcis-9761	162	7	,	,	PUNCT
fcis-9761	162	8	2016	2016	NUM
fcis-9761	162	9	,	,	PUNCT
fcis-9761	162	10	99(3	99(3	NUM
fcis-9761	162	11	):	):	PUNCT
fcis-9761	162	12	773	773	NUM
fcis-9761	162	13	-	-	SYM
fcis-9761	162	14	776	776	NUM
fcis-9761	162	15	.	.	PUNCT
fcis-9761	163	1	[	[	X
fcis-9761	163	2	22	22	NUM
fcis-9761	163	3	]	]	X
fcis-9761	163	4	wang	wang	PROPN
fcis-9761	163	5	z	z	PROPN
fcis-9761	163	6	,	,	PUNCT
fcis-9761	163	7	bovik	bovik	ADV
fcis-9761	163	8	a	a	DET
fcis-9761	163	9	c	c	NOUN
fcis-9761	163	10	,	,	PUNCT
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fcis-9761	163	12	h	h	PROPN
fcis-9761	163	13	r	r	PROPN
fcis-9761	163	14	,	,	PUNCT
fcis-9761	163	15	et	et	PROPN
fcis-9761	163	16	al	al	PROPN
fcis-9761	163	17	.	.	PUNCT
fcis-9761	163	18	image	image	NOUN
fcis-9761	163	19	quality	quality	NOUN
fcis-9761	163	20	assessment	assessment	NOUN
fcis-9761	163	21	:	:	PUNCT
fcis-9761	163	22	from	from	ADP
fcis-9761	163	23	error	error	NOUN
fcis-9761	163	24	visibility	visibility	NOUN
fcis-9761	163	25	to	to	ADP
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fcis-9761	163	27	similarity[j	similarity[j	PROPN
fcis-9761	163	28	]	]	PUNCT
fcis-9761	163	29	.	.	PUNCT
fcis-9761	164	1	ieee	ieee	NOUN
fcis-9761	164	2	transactions	transaction	NOUN
fcis-9761	164	3	on	on	ADP
fcis-9761	164	4	image	image	NOUN
fcis-9761	164	5	processing	processing	NOUN
fcis-9761	164	6	,	,	PUNCT
fcis-9761	164	7	2004	2004	NUM
fcis-9761	164	8	,	,	PUNCT
fcis-9761	164	9	13(4	13(4	NUM
fcis-9761	164	10	):	):	PUNCT
fcis-9761	164	11	600	600	NUM
fcis-9761	164	12	-	-	NUM
fcis-9761	164	13	612	612	NUM
fcis-9761	164	14	.	.	PUNCT
fcis-9761	165	1	[	[	X
fcis-9761	165	2	23	23	NUM
fcis-9761	165	3	]	]	X
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fcis-9761	165	5	d	d	PROPN
fcis-9761	165	6	,	,	PUNCT
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fcis-9761	165	9	,	,	PUNCT
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fcis-9761	165	11	q	q	PROPN
fcis-9761	165	12	,	,	PUNCT
fcis-9761	165	13	et	et	PROPN
fcis-9761	165	14	al	al	PROPN
fcis-9761	165	15	.	.	PROPN
fcis-9761	165	16	gated	gate	VERB
fcis-9761	165	17	context	context	NOUN
fcis-9761	165	18	aggregation	aggregation	NOUN
fcis-9761	165	19	network	network	NOUN
fcis-9761	165	20	for	for	ADP
fcis-9761	165	21	image	image	NOUN
fcis-9761	165	22	dehazing	dehazing	NOUN
fcis-9761	165	23	and	and	CCONJ
fcis-9761	165	24	deraining[c]//	deraining[c]//	ADJ
fcis-9761	165	25	proceedings	proceeding	NOUN
fcis-9761	165	26	of	of	ADP
fcis-9761	165	27	the	the	DET
fcis-9761	165	28	2019	2019	NUM
fcis-9761	165	29	ieee	ieee	NOUN
fcis-9761	165	30	winter	winter	NOUN
fcis-9761	165	31	conference	conference	NOUN
fcis-9761	165	32	on	on	ADP
fcis-9761	165	33	applications	application	NOUN
fcis-9761	165	34	of	of	ADP
fcis-9761	165	35	computer	computer	NOUN
fcis-9761	165	36	vision	vision	NOUN
fcis-9761	165	37	.	.	PUNCT
fcis-9761	166	1	2019	2019	NUM
fcis-9761	166	2	:	:	PUNCT
fcis-9761	166	3	1375	1375	NUM
fcis-9761	166	4	-	-	SYM
fcis-9761	166	5	1383	1383	NUM
fcis-9761	166	6	.	.	PUNCT
fcis-9761	167	1	[	[	X
fcis-9761	167	2	24	24	NUM
fcis-9761	167	3	]	]	X
fcis-9761	167	4	wei	wei	PROPN
fcis-9761	167	5	-	-	PROPN
fcis-9761	167	6	sheng	sheng	PROPN
fcis-9761	167	7	lai	lai	PROPN
fcis-9761	167	8	,	,	PUNCT
fcis-9761	167	9	jia	jia	PROPN
fcis-9761	167	10	-	-	PUNCT
fcis-9761	167	11	bin	bin	PROPN
fcis-9761	167	12	huang	huang	PROPN
fcis-9761	167	13	,	,	PUNCT
fcis-9761	167	14	narendra	narendra	PROPN
fcis-9761	167	15	ahuja	ahuja	PROPN
fcis-9761	167	16	,	,	PUNCT
fcis-9761	167	17	and	and	CCONJ
fcis-9761	167	18	minghsuan	minghsuan	PROPN
fcis-9761	167	19	yang	yang	PROPN
fcis-9761	167	20	.	.	PUNCT
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fcis-9761	168	2	laplacian	laplacian	ADJ
fcis-9761	168	3	pyramid	pyramid	NOUN
fcis-9761	168	4	networks	network	NOUN
fcis-9761	168	5	for	for	ADP
fcis-9761	168	6	fast	fast	ADJ
fcis-9761	168	7	and	and	CCONJ
fcis-9761	168	8	accurate	accurate	ADJ
fcis-9761	168	9	super	super	NOUN
fcis-9761	168	10	-	-	NOUN
fcis-9761	168	11	resolution	resolution	NOUN
fcis-9761	168	12	.	.	PUNCT
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fcis-9761	169	2	cvpr	cvpr	NOUN
fcis-9761	169	3	,	,	PUNCT
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fcis-9761	169	5	624–632	624–632	NUM
fcis-9761	169	6	,	,	PUNCT
fcis-9761	169	7	2017	2017	NUM
fcis-9761	169	8	.	.	PUNCT
fcis-9761	170	1	[	[	X
fcis-9761	170	2	25	25	NUM
fcis-9761	170	3	]	]	X
fcis-9761	170	4	di	di	X
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fcis-9761	170	6	,	,	PUNCT
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fcis-9761	170	8	zhang	zhang	PROPN
fcis-9761	170	9	,	,	PUNCT
fcis-9761	170	10	jingfen	jingfen	PROPN
fcis-9761	170	11	xie	xie	PROPN
fcis-9761	170	12	,	,	PUNCT
fcis-9761	170	13	bin	bin	PROPN
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fcis-9761	170	15	,	,	PUNCT
fcis-9761	170	16	and	and	CCONJ
fcis-9761	170	17	siwei	siwei	PROPN
fcis-9761	170	18	ma.coast	ma.coast	NOUN
fcis-9761	170	19	:	:	PUNCT
fcis-9761	170	20	controllable	controllable	ADJ
fcis-9761	170	21	arbitrary	arbitrary	ADJ
fcis-9761	170	22	-	-	PUNCT
fcis-9761	170	23	sampling	sample	VERB
fcis-9761	170	24	network	network	NOUN
fcis-9761	170	25	for	for	ADP
fcis-9761	170	26	compressive	compressive	ADJ
fcis-9761	170	27	sensing	sensing	NOUN
fcis-9761	170	28	.	.	PUNCT
fcis-9761	171	1	ieee	ieee	NOUN
fcis-9761	171	2	transactions	transaction	NOUN
fcis-9761	171	3	on	on	ADP
fcis-9761	171	4	image	image	NOUN
fcis-9761	171	5	processing	processing	NOUN
fcis-9761	171	6	,	,	PUNCT
fcis-9761	171	7	30	30	NUM
fcis-9761	171	8	:	:	PUNCT
fcis-9761	171	9	6066–6080	6066–6080	NUM
fcis-9761	171	10	,	,	PUNCT
fcis-9761	171	11	2021	2021	NUM
fcis-9761	171	12	.	.	PUNCT