{"id":"https://openalex.org/W4205446812","doi":"https://doi.org/10.1109/vcip53242.2021.9675342","title":"Underwater Image Enhancement with Multi-Scale Residual Attention Network","display_name":"Underwater Image Enhancement with Multi-Scale Residual Attention Network","publication_year":2021,"publication_date":"2021-12-05","ids":{"openalex":"https://openalex.org/W4205446812","doi":"https://doi.org/10.1109/vcip53242.2021.9675342"},"language":"en","primary_location":{"id":"doi:10.1109/vcip53242.2021.9675342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip53242.2021.9675342","pdf_url":null,"source":{"id":"https://openalex.org/S4363608378","display_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","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/A5102269005","display_name":"Yosuke Ueki","orcid":null},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yosuke Ueki","raw_affiliation_strings":["Keio Univ., Yokohama, Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Keio Univ., Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090181402","display_name":"Masaaki Ikehara","orcid":"https://orcid.org/0000-0003-3461-1507"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Ikehara","raw_affiliation_strings":["Keio Univ., Yokohama, Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Keio Univ., Yokohama, Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102269005"],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.196,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.5875576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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":1.0,"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":0.9988999962806702,"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":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.9328869581222534},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7004315257072449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6783063411712646},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6065073013305664},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5920250415802002},{"id":"https://openalex.org/keywords/visibility","display_name":"Visibility","score":0.5360648036003113},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.535617470741272},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5000977516174316},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"Image enhancement","score":0.4770906865596771},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45342209935188293},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4289282262325287},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4273110628128052},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4267594516277313},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.35658931732177734},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35428646206855774},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16492187976837158},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16179987788200378},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.13942530751228333},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09254243969917297},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08215156197547913}],"concepts":[{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.9328869581222534},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7004315257072449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6783063411712646},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6065073013305664},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5920250415802002},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.5360648036003113},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.535617470741272},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5000977516174316},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.4770906865596771},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45342209935188293},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4289282262325287},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4273110628128052},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4267594516277313},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.35658931732177734},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35428646206855774},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16492187976837158},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16179987788200378},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.13942530751228333},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09254243969917297},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08215156197547913},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip53242.2021.9675342","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip53242.2021.9675342","pdf_url":null,"source":{"id":"https://openalex.org/S4363608378","display_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1982471090","https://openalex.org/W2091420866","https://openalex.org/W2128254161","https://openalex.org/W2331128040","https://openalex.org/W2474516010","https://openalex.org/W2587107113","https://openalex.org/W2763503841","https://openalex.org/W2792328492","https://openalex.org/W2794405642","https://openalex.org/W2948400274","https://openalex.org/W2963495494","https://openalex.org/W2963855133","https://openalex.org/W2990176100","https://openalex.org/W2990472756","https://openalex.org/W2998249728","https://openalex.org/W3000775737","https://openalex.org/W3025057169","https://openalex.org/W6637373629","https://openalex.org/W6702130928","https://openalex.org/W6770437327"],"related_works":["https://openalex.org/W3176779361","https://openalex.org/W3163022079","https://openalex.org/W4361733550","https://openalex.org/W2981142287","https://openalex.org/W4390730122","https://openalex.org/W2394308979","https://openalex.org/W4320526406","https://openalex.org/W2219404550","https://openalex.org/W4383097854","https://openalex.org/W4292237644"],"abstract_inverted_index":{"Underwater":[0],"images":[1,59,153],"suffer":[2],"from":[3],"low":[4],"contrast,":[5],"color":[6],"distortion":[7],"and":[8,16,35,85,110,135,140],"visibility":[9],"degradation":[10],"due":[11,60,101],"to":[12,53,61,102,148,150],"the":[13,19,23,62,103,111,114,118,130,180],"light":[14],"scattering":[15],"attenuation.":[17],"Over":[18],"past":[20],"few":[21],"years,":[22],"importance":[24],"of":[25,32,64,75,105,113,138,186],"underwater":[26,36,39,58,65,76,79,124,152],"image":[27,40,80,98,125,170],"enhancement":[28,41,81,126],"has":[29],"increased":[30],"because":[31],"ocean":[33],"engineering":[34],"robotics.":[37],"Existing":[38],"methods":[42,100],"are":[43,69,92,155],"based":[44],"on":[45],"various":[46,151,184],"assumptions.":[47],"However,":[48],"it":[49],"is":[50,166],"almost":[51],"impossible":[52],"define":[54],"appropriate":[55],"assumptions":[56],"for":[57,72,169,183],"diversity":[63],"images.":[66,77,187],"Therefore,":[67],"they":[68,91],"only":[70],"effective":[71,168],"specific":[73],"types":[74,185],"Recently,":[78],"algorisms":[82],"using":[83],"CNNs":[84],"GANS":[86],"have":[87],"been":[88],"proposed,":[89],"but":[90],"not":[93],"as":[94,96],"advanced":[95],"other":[97],"processing":[99],"lack":[104],"suitable":[106],"training":[107],"data":[108],"sets":[109],"complexity":[112],"issues.":[115],"To":[116],"solve":[117],"problems,":[119],"we":[120],"propose":[121],"a":[122],"novel":[123,136],"method":[127,178,182],"which":[128,154,165],"combines":[129],"residual":[131],"feature":[132],"attention":[133],"block":[134],"combination":[137],"multi-scale":[139,163],"multi-patch":[141],"structure.":[142],"Multi-patch":[143],"network":[144,161,164],"extracts":[145],"local":[146],"features":[147],"adjust":[149],"often":[156,167],"Non-homogeneous.":[157],"In":[158],"addition,":[159],"our":[160,176],"includes":[162],"restoration.":[171],"Experimental":[172],"results":[173],"show":[174],"that":[175],"proposed":[177],"outperforms":[179],"conventional":[181]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
