{"id":"https://openalex.org/W7138178488","doi":"https://doi.org/10.1609/aaai.v40i11.37906","title":"Learning Underwater Image Enhancement Iteratively Without Reference Images","display_name":"Learning Underwater Image Enhancement Iteratively Without Reference Images","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138178488","doi":"https://doi.org/10.1609/aaai.v40i11.37906"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i11.37906","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i11.37906","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37906/41868","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37906/41868","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129688975","display_name":"Yi Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I98957242","display_name":"Kitami Institute of Technology","ror":"https://ror.org/05wks2t16","country_code":"JP","type":"education","lineage":["https://openalex.org/I98957242"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yi Tang","raw_affiliation_strings":["Kitami Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Kitami Institute of Technology","institution_ids":["https://openalex.org/I98957242"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068195954","display_name":"Hiroshi Kawasaki","orcid":"https://orcid.org/0000-0001-5825-6066"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Kawasaki","raw_affiliation_strings":["Kyushu University"],"affiliations":[{"raw_affiliation_string":"Kyushu University","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035807965","display_name":"Takafumi Iwaguchi","orcid":"https://orcid.org/0000-0001-9811-0993"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takafumi Iwaguchi","raw_affiliation_strings":["Kyushu University"],"affiliations":[{"raw_affiliation_string":"Kyushu University","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129652274","display_name":"Yuhang Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhang Zhang","raw_affiliation_strings":["Guangzhou University"],"affiliations":[{"raw_affiliation_string":"Guangzhou University","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129748788","display_name":"Hiroshi Masui","orcid":null},"institutions":[{"id":"https://openalex.org/I98957242","display_name":"Kitami Institute of Technology","ror":"https://ror.org/05wks2t16","country_code":"JP","type":"education","lineage":["https://openalex.org/I98957242"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Masui","raw_affiliation_strings":["Kitami Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Kitami Institute of Technology","institution_ids":["https://openalex.org/I98957242"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5129688975"],"corresponding_institution_ids":["https://openalex.org/I98957242"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.5,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"11","first_page":"9457","last_page":"9465"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9567999839782715,"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":0.9567999839782715,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.03579999879002571,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.0010000000474974513,"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/distortion","display_name":"Distortion (music)","score":0.6453999876976013},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.6438999772071838},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5041999816894531},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48809999227523804},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4431000053882599},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4072999954223633},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.37709999084472656},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3653999865055084}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8044999837875366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7003999948501587},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6453999876976013},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.6438999772071838},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5636000037193298},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5041999816894531},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48809999227523804},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4072999954223633},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.37709999084472656},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.36399999260902405},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.30250000953674316},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2996000051498413},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.29789999127388},{"id":"https://openalex.org/C2779495555","wikidata":"https://www.wikidata.org/wiki/Q5148596","display_name":"Color correction","level":3,"score":0.29499998688697815},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C186991048","wikidata":"https://www.wikidata.org/wiki/Q1184883","display_name":"Color difference","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i11.37906","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i11.37906","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37906/41868","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i11.37906","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i11.37906","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/37906/41868","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.6857702136039734}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7138178488.pdf","grobid_xml":"https://content.openalex.org/works/W7138178488.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Since":[0],"high-fidelity":[1],"reference":[2],"images":[3,127],"are":[4,168],"difficult":[5],"to":[6,52,87,96,142,149,172,201],"obtain":[7],"in":[8,60,176],"real":[9],"underwater":[10,35,62,189],"scenes,":[11],"most":[12],"deep":[13],"models":[14],"trained":[15],"by":[16,39],"synthetic":[17],"paired":[18],"data":[19,23],"cannot":[20],"match":[21],"real-world":[22],"exactly.":[24],"In":[25,158],"this":[26],"paper,":[27],"we":[28,64,105],"propose":[29,112],"an":[30,41,107],"unsupervised":[31,67],"training":[32,43],"framework":[33],"for":[34,85,116,155],"image":[36,68],"enhancement":[37,69],"(UIE)":[38],"leveraging":[40],"iterative":[42,162],"strategy":[44],"and":[45,58,76,91,111,137,166],"quantification":[46,114,134],"of":[47,101,179],"specific":[48],"neural":[49,139],"units.":[50],"Specifically,":[51],"eliminate":[53],"the":[54,61,66,89,98,129,133,146,159,177,180],"heavy":[55],"color":[56,77,93,103,117,152,164],"cast":[57,165],"distortion":[59,167],"images,":[63],"decompose":[65],"as":[70],"two":[71],"targeted":[72],"sub-tasks,":[73],"namely":[74],"colorization":[75,86],"compensation.":[78,118],"First,":[79],"a":[80,113,173],"diffusion":[81],"model":[82],"is":[83],"introduced":[84],"correct":[88],"green":[90],"blue":[92],"casts.":[94],"Then,":[95],"intensify":[97],"learning":[99],"ability":[100,148],"balanced":[102,151],"information,":[104],"introduce":[106],"extra":[108,120],"network":[109],"branch":[110,121],"mechanism":[115,135],"The":[119],"encodes":[122],"style":[123],"information":[124],"from":[125],"normal":[126],"into":[128],"generative":[130],"model,":[131],"while":[132],"identifies":[136],"adjusts":[138],"units":[140],"relevant":[141],"warm":[143],"colors,":[144],"improving":[145],"model\u2019s":[147],"learn":[150],"feature":[153],"representations":[154],"robust":[156],"generation.":[157],"end,":[160],"through":[161],"training,":[163],"progressively":[169],"reduced,":[170],"leading":[171],"gradual":[174],"improvement":[175],"quality":[178],"generated":[181],"images.":[182],"Experimental":[183],"results":[184],"on":[185],"various":[186],"widely":[187],"used":[188],"datasets":[190],"demonstrate":[191],"that":[192],"our":[193],"approach":[194],"achieves":[195],"excellent":[196],"performance,":[197],"even":[198],"when":[199],"compared":[200],"recent":[202],"supervised":[203],"methods.":[204]},"counts_by_year":[],"updated_date":"2026-03-20T20:47:17.329874","created_date":"2026-03-18T00:00:00"}
