{"id":"https://openalex.org/W4411701535","doi":"https://doi.org/10.1111/coin.70095","title":"Frequency\u2010Driven Diffusion: A Hierarchical Attention Weighting Framework for Underwater Image Restoration","display_name":"Frequency\u2010Driven Diffusion: A Hierarchical Attention Weighting Framework for Underwater Image Restoration","publication_year":2025,"publication_date":"2025-06-26","ids":{"openalex":"https://openalex.org/W4411701535","doi":"https://doi.org/10.1111/coin.70095"},"language":"en","primary_location":{"id":"doi:10.1111/coin.70095","is_oa":false,"landing_page_url":"https://doi.org/10.1111/coin.70095","pdf_url":null,"source":{"id":"https://openalex.org/S56561474","display_name":"Computational Intelligence","issn_l":"0824-7935","issn":["0824-7935","1467-8640"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence","raw_type":"journal-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":null,"display_name":"Longxiang Deng","orcid":null},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longxiang Deng","raw_affiliation_strings":["Institute of Artificial Intelligence Wuhan University  Wuhan China","National Engineering Research Center for Multimedia Software Wuhan University  Wuhan China","School of Computer Science Wuhan University  Wuhan China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence Wuhan University  Wuhan China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software Wuhan University  Wuhan China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science Wuhan University  Wuhan China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072913037","display_name":"Laibin Chang","orcid":"https://orcid.org/0000-0002-6510-4359"},"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"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Laibin Chang","raw_affiliation_strings":["Institute of Artificial Intelligence Wuhan University  Wuhan China","National Engineering Research Center for Multimedia Software Wuhan University  Wuhan China","School of Computer Science Wuhan University  Wuhan China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence Wuhan University  Wuhan China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"National Engineering Research Center for Multimedia Software Wuhan University  Wuhan China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science Wuhan University  Wuhan China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062908102","display_name":"Wei Liu","orcid":"https://orcid.org/0000-0003-2968-2888"},"institutions":[{"id":"https://openalex.org/I862669128","display_name":"Xiaomi (China)","ror":"https://ror.org/029f7bn57","country_code":"CN","type":"company","lineage":["https://openalex.org/I862669128"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Xiaomi Corporation  Beijing China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiaomi Corporation  Beijing China","institution_ids":["https://openalex.org/I862669128"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062908102","https://openalex.org/A5072913037"],"corresponding_institution_ids":["https://openalex.org/I37461747","https://openalex.org/I862669128"],"apc_list":{"value":3450,"currency":"USD","value_usd":3450},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11534728,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"41","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T11019","display_name":"Image Enhancement Techniques","score":0.9998000264167786,"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":0.9994000196456909,"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/weighting","display_name":"Weighting","score":0.6256447434425354},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.6169633269309998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48325687646865845},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.4568120241165161},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.439081609249115},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4244460165500641},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.40612274408340454},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4004102349281311},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3342753052711487},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.24489542841911316},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.1754591166973114},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.11950275301933289},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11313700675964355}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6256447434425354},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.6169633269309998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48325687646865845},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.4568120241165161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.439081609249115},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4244460165500641},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.40612274408340454},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4004102349281311},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3342753052711487},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.24489542841911316},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.1754591166973114},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.11950275301933289},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11313700675964355},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/coin.70095","is_oa":false,"landing_page_url":"https://doi.org/10.1111/coin.70095","pdf_url":null,"source":{"id":"https://openalex.org/S56561474","display_name":"Computational Intelligence","issn_l":"0824-7935","issn":["0824-7935","1467-8640"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1493215903","https://openalex.org/W1522301498","https://openalex.org/W1644173899","https://openalex.org/W2073151603","https://openalex.org/W2133665775","https://openalex.org/W2293581118","https://openalex.org/W2763503841","https://openalex.org/W2899190185","https://openalex.org/W2990176100","https://openalex.org/W3006777311","https://openalex.org/W3009406242","https://openalex.org/W3036167779","https://openalex.org/W3099025816","https://openalex.org/W3186571640","https://openalex.org/W3194942914","https://openalex.org/W4282914989","https://openalex.org/W4285821234","https://openalex.org/W4317470160","https://openalex.org/W4318455600","https://openalex.org/W4377079715","https://openalex.org/W4379255977","https://openalex.org/W4383812791","https://openalex.org/W4385299561","https://openalex.org/W4385848801","https://openalex.org/W4385988004","https://openalex.org/W4386148309","https://openalex.org/W4386702784","https://openalex.org/W4387969013","https://openalex.org/W4387987031","https://openalex.org/W4389347891","https://openalex.org/W4389992741","https://openalex.org/W4391520444","https://openalex.org/W4393147889","https://openalex.org/W4394629801","https://openalex.org/W4400648070","https://openalex.org/W4403533023","https://openalex.org/W4405864600","https://openalex.org/W4406047518","https://openalex.org/W4406270904","https://openalex.org/W4409346485","https://openalex.org/W4410253654","https://openalex.org/W6779823529"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2049003611","https://openalex.org/W2127804977","https://openalex.org/W3176779361","https://openalex.org/W3163022079","https://openalex.org/W2966501856","https://openalex.org/W2974904990","https://openalex.org/W2365681766","https://openalex.org/W2393963626"],"abstract_inverted_index":{"ABSTRACT":[0],"Underwater":[1,50],"images":[2],"often":[3],"suffer":[4],"from":[5,23],"visual":[6],"degradation,":[7,101],"affecting":[8],"downstream":[9],"tasks.":[10],"While":[11],"recent":[12],"underwater":[13],"image":[14,45,57,83,100],"enhancement":[15],"(UIE)":[16],"techniques":[17],"have":[18],"made":[19],"some":[20],"advances":[21],"benefiting":[22],"deep":[24],"neural":[25],"networks,":[26],"challenges":[27],"remain":[28],"in":[29,44,125,169],"restoring":[30],"fine":[31,137],"details":[32],"and":[33,74,86,97,146,153,172],"achieving":[34],"computational":[35,104],"efficiency.":[36],"Inspired":[37],"by":[38],"the":[39,49,62,66,81,90,94,113,121],"success":[40],"of":[41,65],"diffusion":[42],"models":[43],"generation,":[46],"we":[47,111],"propose":[48],"Laplacian\u2010Guided":[51],"Diffusion":[52],"Model":[53],"(ULDM),":[54],"which":[55],"enhances":[56],"features":[58,149],"layer\u2010by\u2010layer":[59,133],"based":[60],"on":[61],"hierarchical":[63,155],"structure":[64],"Laplacian":[67,78],"pyramid":[68,79],"transform":[69],"to":[70,92,134],"achieve":[71],"both":[72,170],"high\u2010quality":[73],"efficient":[75],"UIE.":[76],"The":[77],"decomposes":[80],"degraded":[82],"into":[84],"high\u2010":[85],"low\u2010frequency":[87,95],"components,":[88],"enabling":[89],"model":[91],"denoise":[93],"spectrum":[96],"address":[98],"global":[99],"thereby":[102],"reducing":[103],"overhead.":[105],"To":[106],"efficiently":[107],"enhance":[108],"high\u2010frequency":[109,126,140],"details,":[110],"introduce":[112],"Hierarchical":[114],"Attention":[115],"Weighted":[116],"Module":[117],"(HAWM)":[118],"that":[119,164],"leverages":[120],"strong":[122,143],"pixel":[123,144],"correlations":[124],"sub\u2010images":[127,141],"at":[128],"different":[129,151],"levels,":[130],"adjusting":[131],"them":[132],"better":[135],"capture":[136],"details.":[138],"These":[139],"exhibit":[142],"correlation":[145],"consistent":[147],"texture":[148],"across":[150],"layers,":[152],"their":[154],"pattern":[156],"ensures":[157],"effective":[158],"detail":[159],"restoration.":[160],"Extensive":[161],"experiments":[162],"demonstrate":[163],"ULDM":[165],"outperforms":[166],"state\u2010of\u2010the\u2010art":[167],"methods":[168],"quantitative":[171],"qualitative":[173],"evaluations.":[174]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
