{"id":"https://openalex.org/W4310418676","doi":"https://doi.org/10.1145/3571600.3571630","title":"Towards Realistic Underwater Dataset Generation and Color Restoration\u2731","display_name":"Towards Realistic Underwater Dataset Generation and Color Restoration\u2731","publication_year":2022,"publication_date":"2022-12-08","ids":{"openalex":"https://openalex.org/W4310418676","doi":"https://doi.org/10.1145/3571600.3571630"},"language":"en","primary_location":{"id":"doi:10.1145/3571600.3571630","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3571600.3571630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2211.14821","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024587699","display_name":"Neham Jain","orcid":"https://orcid.org/0000-0002-0898-8856"},"institutions":[{"id":"https://openalex.org/I1310264347","display_name":"IIT Research Institute","ror":"https://ror.org/057jp7h82","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1310264347"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Neham Jain","raw_affiliation_strings":["IIT Madras, IN"],"affiliations":[{"raw_affiliation_string":"IIT Madras, IN","institution_ids":["https://openalex.org/I1310264347"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066528821","display_name":"Gopi Raju Matta","orcid":"https://orcid.org/0000-0003-3305-3136"},"institutions":[{"id":"https://openalex.org/I1310264347","display_name":"IIT Research Institute","ror":"https://ror.org/057jp7h82","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1310264347"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gopi Raju Matta","raw_affiliation_strings":["IIT Madras, IN"],"affiliations":[{"raw_affiliation_string":"IIT Madras, IN","institution_ids":["https://openalex.org/I1310264347"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006862080","display_name":"Kaushik Mitra","orcid":"https://orcid.org/0000-0001-6747-9050"},"institutions":[{"id":"https://openalex.org/I1310264347","display_name":"IIT Research Institute","ror":"https://ror.org/057jp7h82","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1310264347"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kaushik Mitra","raw_affiliation_strings":["IIT Madras, IN"],"affiliations":[{"raw_affiliation_string":"IIT Madras, IN","institution_ids":["https://openalex.org/I1310264347"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5024587699"],"corresponding_institution_ids":["https://openalex.org/I1310264347"],"apc_list":null,"apc_paid":null,"fwci":0.5098,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64815154,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9968000054359436,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9954000115394592,"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/underwater","display_name":"Underwater","score":0.8611076474189758},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7959966659545898},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6916666030883789},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6506723165512085},{"id":"https://openalex.org/keywords/color-correction","display_name":"Color correction","score":0.5671566724777222},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48765552043914795},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.46742719411849976},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4652838110923767},{"id":"https://openalex.org/keywords/attenuation","display_name":"Attenuation","score":0.45978644490242004},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4297892451286316},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24880573153495789},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.14816814661026},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09279420971870422},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.07737189531326294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07212406396865845}],"concepts":[{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.8611076474189758},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7959966659545898},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6916666030883789},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6506723165512085},{"id":"https://openalex.org/C2779495555","wikidata":"https://www.wikidata.org/wiki/Q5148596","display_name":"Color correction","level":3,"score":0.5671566724777222},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48765552043914795},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.46742719411849976},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4652838110923767},{"id":"https://openalex.org/C184652730","wikidata":"https://www.wikidata.org/wiki/Q2357982","display_name":"Attenuation","level":2,"score":0.45978644490242004},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4297892451286316},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24880573153495789},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.14816814661026},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09279420971870422},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.07737189531326294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07212406396865845},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3571600.3571630","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3571600.3571630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2211.14821","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.14821","pdf_url":"https://arxiv.org/pdf/2211.14821","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2211.14821","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2211.14821","pdf_url":"https://arxiv.org/pdf/2211.14821","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","display_name":"Life below water","score":0.7699999809265137}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1901129140","https://openalex.org/W2055447163","https://openalex.org/W2091420866","https://openalex.org/W2094185466","https://openalex.org/W2126926806","https://openalex.org/W2133665775","https://openalex.org/W2181646778","https://openalex.org/W2331128040","https://openalex.org/W2474516010","https://openalex.org/W2512018227","https://openalex.org/W2523532944","https://openalex.org/W2587107113","https://openalex.org/W2603777577","https://openalex.org/W2763503841","https://openalex.org/W2794405642","https://openalex.org/W2798898057","https://openalex.org/W2884585870","https://openalex.org/W2950055287","https://openalex.org/W2963890275","https://openalex.org/W2964088115","https://openalex.org/W2971483169","https://openalex.org/W2990176100","https://openalex.org/W2997763120","https://openalex.org/W3006777311","https://openalex.org/W3009406242","https://openalex.org/W3157502174","https://openalex.org/W3159660641","https://openalex.org/W3170697543","https://openalex.org/W3205494421","https://openalex.org/W4283808395","https://openalex.org/W6753412334"],"related_works":["https://openalex.org/W4226332782","https://openalex.org/W3176779361","https://openalex.org/W3163022079","https://openalex.org/W4389777547","https://openalex.org/W2966516593","https://openalex.org/W4313029978","https://openalex.org/W2616936297","https://openalex.org/W4383108568","https://openalex.org/W4323651220","https://openalex.org/W1540776626"],"abstract_inverted_index":{"Recovery":[0],"of":[1,131],"true":[2],"color":[3,21,49,151],"from":[4,107],"underwater":[5,57,65,109,113,132],"images":[6,106],"is":[7,12,36],"an":[8,88],"ill-posed":[9],"problem.":[10],"This":[11,67],"because":[13],"the":[14,19,72,96,99],"wide-band":[15],"attenuation":[16],"coefficients":[17],"for":[18],"RGB":[20],"channels":[22],"depend":[23],"on":[24,55,63,144],"object":[25],"range,":[26],"reflectance,":[27],"etc.":[28],"which":[29,52],"are":[30,53],"difficult":[31],"to":[32,39,71,90,94,111,149],"model.":[33],"Also,":[34],"there":[35],"backscattering":[37],"due":[38],"suspended":[40],"particles":[41],"in":[42],"water.":[43],"Thus,":[44],"most":[45],"existing":[46],"deep-learning":[47],"based":[48,142],"restoration":[50],"methods,":[51],"trained":[54],"synthetic":[56,75,100,108],"datasets,":[58],"do":[59],"not":[60],"perform":[61,150],"well":[62],"real":[64,80,102,112],"data.":[66],"can":[68,126,157],"be":[69,158],"attributed":[70],"fact":[73],"that":[74,125],"data":[76],"cannot":[77],"accurately":[78],"represent":[79],"conditions.":[81,133],"To":[82],"address":[83],"this":[84,116],"issue,":[85],"we":[86,121],"use":[87],"image":[89,91],"translation":[92],"network":[93,143],"bridge":[95],"gap":[97],"between":[98],"and":[101,154],"domains":[103],"by":[104],"translating":[105],"domain":[110,118,146],"domain.":[114],"Using":[115],"multimodal":[117],"adaptation":[119],"technique,":[120],"create":[122],"a":[123,128,137],"dataset":[124,148],"capture":[127],"diverse":[129],"array":[130],"We":[134],"then":[135],"train":[136],"simple":[138],"but":[139],"effective":[140],"CNN":[141],"our":[145],"adapted":[147],"restoration.":[152],"Code":[153],"pre-trained":[155],"models":[156],"accessed":[159],"at":[160],"https://github.com/nehamjain10/TRUDGCR":[161]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}