{"id":"https://openalex.org/W2620976957","doi":"https://doi.org/10.1109/lsp.2017.2710233","title":"Primal-Dual Plug-and-Play Image Restoration","display_name":"Primal-Dual Plug-and-Play Image Restoration","publication_year":2017,"publication_date":"2017-05-31","ids":{"openalex":"https://openalex.org/W2620976957","doi":"https://doi.org/10.1109/lsp.2017.2710233","mag":"2620976957"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2017.2710233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2710233","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5040341698","display_name":"Shunsuke Ono","orcid":"https://orcid.org/0000-0001-7890-5131"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shunsuke Ono","raw_affiliation_strings":["Laboratory for Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5040341698"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":6.1927,"has_fulltext":false,"cited_by_count":162,"citation_normalized_percentile":{"value":0.97797399,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"24","issue":"8","first_page":"1108","last_page":"1112"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9993000030517578,"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/image-restoration","display_name":"Image restoration","score":0.8142379522323608},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6187556982040405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5707825422286987},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.5358719825744629},{"id":"https://openalex.org/keywords/plug-in","display_name":"Plug-in","score":0.5025246143341064},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42353928089141846},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4078754782676697},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38209235668182373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30409878492355347},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2879631519317627}],"concepts":[{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.8142379522323608},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6187556982040405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5707825422286987},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5358719825744629},{"id":"https://openalex.org/C4924752","wikidata":"https://www.wikidata.org/wiki/Q184148","display_name":"Plug-in","level":2,"score":0.5025246143341064},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42353928089141846},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4078754782676697},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38209235668182373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30409878492355347},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2879631519317627},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2017.2710233","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2710233","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G3362068425","display_name":null,"funder_award_id":"15H06197","funder_id":"https://openalex.org/F4320320212","funder_display_name":"Japan Society for the Promotion of Science London"}],"funders":[{"id":"https://openalex.org/F4320320212","display_name":"Japan Society for the Promotion of Science London","ror":"https://ror.org/02m7axw05"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1547941176","https://openalex.org/W1667895010","https://openalex.org/W1922442141","https://openalex.org/W1927306724","https://openalex.org/W1963865224","https://openalex.org/W1973665846","https://openalex.org/W1979072167","https://openalex.org/W1998991750","https://openalex.org/W2004346156","https://openalex.org/W2033603511","https://openalex.org/W2038877243","https://openalex.org/W2045079045","https://openalex.org/W2056370875","https://openalex.org/W2058005980","https://openalex.org/W2058532290","https://openalex.org/W2087416986","https://openalex.org/W2092663520","https://openalex.org/W2097073572","https://openalex.org/W2100705753","https://openalex.org/W2114423093","https://openalex.org/W2116857329","https://openalex.org/W2123031198","https://openalex.org/W2125852763","https://openalex.org/W2142058898","https://openalex.org/W2142280715","https://openalex.org/W2147068866","https://openalex.org/W2148791483","https://openalex.org/W2156242833","https://openalex.org/W2156523995","https://openalex.org/W2296055064","https://openalex.org/W2396831964","https://openalex.org/W2418010766","https://openalex.org/W2466977012","https://openalex.org/W2578004414","https://openalex.org/W2594827121","https://openalex.org/W2610222908","https://openalex.org/W2628520183","https://openalex.org/W2765202580","https://openalex.org/W2963814976","https://openalex.org/W2964137109","https://openalex.org/W2964261957","https://openalex.org/W3100727723","https://openalex.org/W3105425607","https://openalex.org/W3106359998","https://openalex.org/W3121742466","https://openalex.org/W4229650096","https://openalex.org/W4246327874","https://openalex.org/W4292363360","https://openalex.org/W6737365603","https://openalex.org/W6745193812"],"related_works":["https://openalex.org/W4287378204","https://openalex.org/W2981957539","https://openalex.org/W47352601","https://openalex.org/W2545422590","https://openalex.org/W4240705470","https://openalex.org/W2945311252","https://openalex.org/W2006843870","https://openalex.org/W1602455006","https://openalex.org/W2365681766","https://openalex.org/W2393963626"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,44,55,71,77,82,97,102,132],"new":[3],"plug-and-play":[4,13,56,61,135],"image":[5,14,51,117,136],"restoration":[6,15,52,137],"method":[7,30,48,74,145],"based":[8],"on":[9],"primal-dual":[10,129],"splitting.":[11],"Existing":[12],"methods":[16],"interpret":[17],"any":[18],"off-the-shelf":[19],"Gaussian":[20,46],"denoiser":[21],"as":[22,162],"one":[23],"step":[24],"of":[25,31,42,96,128,170],"the":[26,40,59,94,126,143,159,165,168],"so-called":[27],"alternating":[28],"direction":[29],"multipliers":[32],"(ADMM).":[33],"This":[34],"makes":[35],"it":[36,68,89,107,157],"possible":[37],"to":[38,92,111],"exploit":[39],"power":[41],"such":[43],"highly-customized":[45],"denoising":[47],"for":[49,116],"general":[50],"tasks":[53],"in":[54,75,81,164],"fashion.":[57],"However,":[58],"ADMM-based":[60],"approach":[62,120],"(ADMMPnP)":[63],"has":[64],"several":[65],"limitations:":[66],"1)":[67],"often":[69],"requires":[70],"problem-specific":[72],"iterative":[73],"solving":[76],"subproblem,":[78],"which":[79],"results":[80,140],"computationally":[83],"expensive":[84],"inner":[85,154],"loop;":[86],"and":[87],"2)":[88],"is":[90,146],"specialized":[91],"handle":[93],"formulation":[95],"regularization":[98],"(plug-and-play)":[99],"term":[100],"plus":[101],"data-fidelity":[103],"term,":[104],"so":[105],"that":[106,142],"does":[108],"not":[109],"allow":[110],"impose":[112],"hard":[113],"constraints":[114],"useful":[115],"restoration.":[118],"Our":[119],"resolves":[121],"these":[122],"issues":[123],"by":[124],"leveraging":[125],"nature":[127],"splitting,":[130],"yielding":[131],"very":[133],"flexible":[134],"method.":[138],"Experimental":[139],"demonstrate":[141],"proposed":[144],"much":[147],"more":[148],"efficient":[149],"than":[150],"ADMMPnP":[151,163,171],"with":[152],"an":[153],"loop,":[155],"whereas":[156],"keeps":[158],"same":[160],"efficiency":[161],"case":[166],"where":[167],"subproblem":[169],"can":[172],"be":[173],"solved":[174],"efficiently.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":27},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":22},{"year":2020,"cited_by_count":23},{"year":2019,"cited_by_count":26},{"year":2018,"cited_by_count":15},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-05-29T09:21:14.243279","created_date":"2025-10-10T00:00:00"}