{"id":"https://openalex.org/W3198202938","doi":"https://doi.org/10.1109/tmm.2021.3094058","title":"DBDnet: A Deep Boosting Strategy for Image Denoising","display_name":"DBDnet: A Deep Boosting Strategy for Image Denoising","publication_year":2021,"publication_date":"2021-07-01","ids":{"openalex":"https://openalex.org/W3198202938","doi":"https://doi.org/10.1109/tmm.2021.3094058","mag":"3198202938"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2021.3094058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3094058","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","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":"https://openalex.org/A5040010053","display_name":"Jiayi Ma","orcid":"https://orcid.org/0000-0003-3264-3265"},"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":"Jiayi Ma","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053368234","display_name":"Chengli Peng","orcid":"https://orcid.org/0000-0001-6042-3871"},"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":"Chengli Peng","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091353529","display_name":"Xin Tian","orcid":"https://orcid.org/0000-0003-1993-2708"},"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":"Xin Tian","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087165831","display_name":"Junjun Jiang","orcid":"https://orcid.org/0000-0002-5694-505X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjun Jiang","raw_affiliation_strings":["School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5040010053"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":2.6161,"has_fulltext":false,"cited_by_count":38,"citation_normalized_percentile":{"value":0.91584014,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"24","issue":null,"first_page":"3157","last_page":"3168"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9965999722480774,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.995199978351593,"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/noise-reduction","display_name":"Noise reduction","score":0.8267455101013184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7153620719909668},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6758347749710083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6449087262153625},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5697577595710754},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.56564861536026},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.5350040197372437},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.45501744747161865},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4391924738883972},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.4133545756340027},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25107327103614807},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.2450416088104248},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06391298770904541}],"concepts":[{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.8267455101013184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7153620719909668},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6758347749710083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6449087262153625},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5697577595710754},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.56564861536026},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.5350040197372437},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.45501744747161865},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4391924738883972},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.4133545756340027},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25107327103614807},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.2450416088104248},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06391298770904541}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2021.3094058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2021.3094058","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4099999964237213,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1017338546","display_name":null,"funder_award_id":"2019CFA037","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G3260984976","display_name":null,"funder_award_id":"61773295","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8308266195","display_name":null,"funder_award_id":"61971315","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1906770428","https://openalex.org/W1978749115","https://openalex.org/W1998419211","https://openalex.org/W2011181254","https://openalex.org/W2033468335","https://openalex.org/W2037642501","https://openalex.org/W2038174831","https://openalex.org/W2056370875","https://openalex.org/W2090571884","https://openalex.org/W2097713019","https://openalex.org/W2103559027","https://openalex.org/W2130184048","https://openalex.org/W2153663612","https://openalex.org/W2194775991","https://openalex.org/W2274609130","https://openalex.org/W2319794630","https://openalex.org/W2469031810","https://openalex.org/W2508457857","https://openalex.org/W2536599074","https://openalex.org/W2608488581","https://openalex.org/W2610691757","https://openalex.org/W2613763509","https://openalex.org/W2613941322","https://openalex.org/W2764207251","https://openalex.org/W2765333864","https://openalex.org/W2771305881","https://openalex.org/W2777598052","https://openalex.org/W2784344583","https://openalex.org/W2888395215","https://openalex.org/W2894629025","https://openalex.org/W2918288062","https://openalex.org/W2946561582","https://openalex.org/W2952323569","https://openalex.org/W2952762034","https://openalex.org/W2955354750","https://openalex.org/W2962767526","https://openalex.org/W2963317244","https://openalex.org/W2963446712","https://openalex.org/W2963725279","https://openalex.org/W2963800716","https://openalex.org/W2964215687","https://openalex.org/W2971061988","https://openalex.org/W2971719842","https://openalex.org/W2995224431","https://openalex.org/W2999653953","https://openalex.org/W3000255543","https://openalex.org/W3033835243","https://openalex.org/W3034504121","https://openalex.org/W3041976821","https://openalex.org/W3042698524","https://openalex.org/W3099211682","https://openalex.org/W3101559505","https://openalex.org/W3104724358","https://openalex.org/W4213262319","https://openalex.org/W6674855086","https://openalex.org/W6730160095","https://openalex.org/W6749488094","https://openalex.org/W6767022471","https://openalex.org/W6783019922","https://openalex.org/W6784847106"],"related_works":["https://openalex.org/W1911817635","https://openalex.org/W2810224748","https://openalex.org/W2353656796","https://openalex.org/W2011915004","https://openalex.org/W2124371593","https://openalex.org/W2090859501","https://openalex.org/W2955414824","https://openalex.org/W2033757130","https://openalex.org/W2545294132","https://openalex.org/W4297491189"],"abstract_inverted_index":{"In":[0,35,129,190,220],"this":[1,89,102],"paper,":[2],"we":[3,104,131,222],"propose":[4,140],"a":[5,21,28,32,40,45,56,109],"new":[6],"deep":[7,11,228],"network":[8,24],"architecture":[9],"named":[10],"boosting":[12,57,229],"denoising":[13,107,177,188,195,199,239,244],"net":[14],"(DBDnet)":[15],"for":[16,192],"image":[17,187,198,238],"denoising.":[18],"It":[19],"is":[20,119,248],"residual":[22],"learning":[23],"that":[25,68,171,226],"can":[26,174,231],"generate":[27],"noise":[29,42,52,70,81,90,96,98,127,164],"map":[30,43,53,71],"from":[31,65,124],"noisy":[33],"observation.":[34],"detail,":[36],"it":[37,147],"first":[38],"generates":[39],"coarse":[41,126],"via":[44,55],"simple":[46],"structure,":[47],"and":[48,114,139,165,196,216,224,241],"then":[49],"updates":[50],"the":[51,66,69,79,106,115,122,125,133,151,193,201,205,227,236],"gradually":[54],"function.":[58],"The":[59],"motivation":[60],"of":[61,97,111,117,135,160,186,204],"our":[62,172,210],"DBDnet":[63,118,153,173,211],"stems":[64],"observation":[67],"recovered":[72],"by":[73,157,209],"any":[74],"algorithm":[75],"cannot":[76],"ideally":[77],"equal":[78],"ground-truth":[80],"map,":[82],"which":[83],"typically":[84],"contains":[85],"noise.":[86,167],"We":[87,149],"call":[88],"NoN,":[91,113],"<italic":[92],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[93,253],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i.e.</i>":[94],",":[95],"map.":[99,128],"Based":[100],"on":[101,154,183],"observation,":[103],"formulate":[105],"as":[108],"process":[110,134],"reducing":[112,136],"role":[116],"to":[120,145],"eliminate":[121],"NoN":[123,137,142],"particular,":[130,191],"analyze":[132],"theoretically,":[138],"an":[141],"eliminating":[143],"module":[144],"simulate":[146],"accordingly.":[148],"evaluate":[150],"proposed":[152],"images":[155],"polluted":[156],"different":[158],"levels":[159],"additive":[161],"white":[162],"Gaussian":[163,194],"real":[166,197],"Experiment":[168],"results":[169],"demonstrate":[170],"attain":[175],"better":[176],"performance":[178],"compared":[179],"with":[180],"state-of-the-art":[181,237],"methods":[182],"several":[184],"kinds":[185],"tasks.":[189],"tasks,":[200],"average":[202],"improvements":[203],"PSNR":[206],"values":[207],"brought":[208],"are":[212],"about":[213],"0.25":[214],"dB":[215],"1.01":[217],"dB,":[218],"respectively.":[219],"addition,":[221],"find":[223],"verify":[225],"insight":[230],"be":[232],"easily":[233],"introduced":[234],"into":[235],"network,":[240],"promotes":[242],"its":[243],"performance.":[245],"Our":[246],"code":[247],"publicly":[249],"available":[250],"at":[251],"<uri":[252],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/jiayi-ma/DBDNet</uri>":[254],".":[255]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":8}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}