{"id":"https://openalex.org/W3129807154","doi":"https://doi.org/10.1109/igarss39084.2020.9324099","title":"A Method to Create Training Dataset for Dehazing with Cyclegan","display_name":"A Method to Create Training Dataset for Dehazing with Cyclegan","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3129807154","doi":"https://doi.org/10.1109/igarss39084.2020.9324099","mag":"3129807154"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9324099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324099","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100323550","display_name":"Hui Zhang","orcid":"https://orcid.org/0000-0003-2989-7547"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hui Zhang","raw_affiliation_strings":["Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC"],"affiliations":[{"raw_affiliation_string":"Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016478003","display_name":"Fan Mou","orcid":null},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Mou","raw_affiliation_strings":["School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, PRC"],"affiliations":[{"raw_affiliation_string":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, PRC","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051307775","display_name":"Shangqi Duan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shangqi Duan","raw_affiliation_strings":["Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC"],"affiliations":[{"raw_affiliation_string":"Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053490485","display_name":"Shuangde Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shuangde Huang","raw_affiliation_strings":["Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC"],"affiliations":[{"raw_affiliation_string":"Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439224","display_name":"Shengwei Wang","orcid":"https://orcid.org/0000-0002-9684-590X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shengwei Wang","raw_affiliation_strings":["Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC"],"affiliations":[{"raw_affiliation_string":"Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017927466","display_name":"Debin Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Debin Xu","raw_affiliation_strings":["Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC"],"affiliations":[{"raw_affiliation_string":"Kunming Power Supply Bureau of Yunnan Power Grid Co., Ltd., Kunming, Yunnan, PRC","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083627327","display_name":"Zezhong Zheng","orcid":"https://orcid.org/0000-0002-5615-5015"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"funder","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]},{"id":"https://openalex.org/I38706770","display_name":"Guilin University of Technology","ror":"https://ror.org/03z391397","country_code":"CN","type":"education","lineage":["https://openalex.org/I38706770"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zezhong Zheng","raw_affiliation_strings":["Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, PRC","Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen, Guangdong, PRC","School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, PRC","State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing, PRC","State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, PRC"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin, Guangxi, PRC","institution_ids":["https://openalex.org/I38706770"]},{"raw_affiliation_string":"Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen, Guangdong, PRC","institution_ids":["https://openalex.org/I211433327"]},{"raw_affiliation_string":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu, Sichuan, PRC","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing, PRC","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941","https://openalex.org/I4210128053"]},{"raw_affiliation_string":"State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei, PRC","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100323550"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1954,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.52544196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"6997","last_page":"7000"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8761561512947083},{"id":"https://openalex.org/keywords/haze","display_name":"Haze","score":0.751488208770752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7254868149757385},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6219519972801208},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.58555668592453},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5817925333976746},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5756576657295227},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5407575964927673},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48655954003334045},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4795496165752411},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47064322233200073},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4534185528755188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3759004473686218}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8761561512947083},{"id":"https://openalex.org/C79974267","wikidata":"https://www.wikidata.org/wiki/Q643546","display_name":"Haze","level":2,"score":0.751488208770752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7254868149757385},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6219519972801208},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.58555668592453},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5817925333976746},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5756576657295227},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5407575964927673},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48655954003334045},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4795496165752411},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47064322233200073},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4534185528755188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3759004473686218},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9324099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324099","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G8586823583","display_name":null,"funder_award_id":"KF-2019-04-074,KF-2019-04-069,KF-2018-03-063","funder_id":"https://openalex.org/F4320310282","funder_display_name":"Ministry of Natural Resources"}],"funders":[{"id":"https://openalex.org/F4320310282","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02ntv3742"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2128254161","https://openalex.org/W2256362396","https://openalex.org/W2536722097","https://openalex.org/W2779176852","https://openalex.org/W2919115771","https://openalex.org/W2962793481","https://openalex.org/W6647720530"],"related_works":["https://openalex.org/W2397673276","https://openalex.org/W2318437963","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W3000197790"],"abstract_inverted_index":{"Haze":[0],"usually":[1,37],"blurs":[2],"the":[3,25,35,39,44,81,86,120,126,163,168,175,196,199,206,210,216,223,230,241,244,254],"characteristics":[4],"of":[5,27,31,53,111,154,177,243],"images":[6,99,104,108,151,164,170,189,202],"shotted":[7],"in":[8],"adverse":[9],"weather":[10],"conditions.":[11],"It":[12],"brings":[13],"many":[14],"challenges":[15],"for":[16,68,96],"computer":[17],"vision":[18],"such":[19],"as":[20,185,195,205],"object":[21],"detection.":[22],"Due":[23],"to":[24,59,91,124,132,208,214,239],"lack":[26],"effective":[28,57],"training":[29,54,61,94,178],"dataset":[30,62,95,121,179,182,221],"remote":[32,69,97],"sensing":[33,70,98],"image,":[34,246],"dehazing":[36,217,224],"utilize":[38],"physical":[40,87],"model":[41,137],"rather":[42,84],"than":[43,85],"deep":[45],"learning":[46],"approach":[47,78,236],"based":[48,79],"on":[49,80],"a":[50,76,93,141,145],"large":[51],"number":[52],"dataset.":[55],"An":[56],"method":[58],"create":[60,92],"may":[63],"provide":[64],"some":[65],"new":[66],"ideas":[67],"image":[71,135,143],"dehazing.":[72,100],"In":[73],"this":[74],"paper,":[75],"novel":[77],"visual":[82],"features":[83],"counterparts":[88],"is":[89,183,237,249],"developed":[90],"Firstly,":[101],"400":[102,106],"haze":[103,146,169,188],"and":[105,162,180,198,222,229],"clear":[107,142,150,201],"with":[109,152,171],"size":[110,153],"240\u00d7240":[112,155],"pixels":[113,156],"were":[114,157,165,193,203,227],"gathered":[115],"from":[116,159],"Landsat":[117,160],"8.":[118],"Secondly,":[119],"was":[122],"utilized":[123],"train":[125,209],"cycle-consistent":[127],"generative":[128],"adversarial":[129],"network":[130],"(CycleGAN)":[131],"derive":[133,215],"an":[134],"transform":[136],"which":[138],"can":[139],"convert":[140],"into":[144,167],"one.":[147],"Thirdly,":[148],"4000":[149],"collected":[158],"8":[161],"transformed":[166],"our":[172,235],"model.":[173],"Finally,":[174],"ratio":[176],"testing":[181],"set":[184],"4:1.":[186],"The":[187,219],"created":[190,220],"by":[191],"us":[192],"selected":[194],"input":[197],"original":[200,245],"chosen":[204],"output":[207],"convolutional":[211],"neural":[212],"networks":[213],"models.":[218],"models":[225],"derived":[226],"tested,":[228],"experimental":[231],"results":[232],"showed":[233],"that":[234],"better":[238],"keep":[240],"brightnessinformation":[242],"but":[247],"it":[248],"not":[250],"good":[251],"at":[252],"keeping":[253],"chroma":[255],"information.":[256]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
