{"id":"https://openalex.org/W2061645416","doi":"https://doi.org/10.1109/tip.2014.2362051","title":"Iterative Support Detection-Based Split Bregman Method for Wavelet Frame-Based Image Inpainting","display_name":"Iterative Support Detection-Based Split Bregman Method for Wavelet Frame-Based Image Inpainting","publication_year":2014,"publication_date":"2014-10-08","ids":{"openalex":"https://openalex.org/W2061645416","doi":"https://doi.org/10.1109/tip.2014.2362051","mag":"2061645416","pmid":"https://pubmed.ncbi.nlm.nih.gov/25312924"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2014.2362051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2014.2362051","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5022895441","display_name":"Liangtian He","orcid":"https://orcid.org/0000-0002-1300-1892"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liangtian He","raw_affiliation_strings":["School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China","School of Mathematical Sciences University of Electronic Science and Technology of China  Chengdu China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Mathematical Sciences University of Electronic Science and Technology of China  Chengdu China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100694459","display_name":"Yilun Wang","orcid":"https://orcid.org/0000-0002-7324-6007"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilun Wang","raw_affiliation_strings":["School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China","School of Mathematical Sciences University of Electronic Science and Technology of China  Chengdu China"],"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]},{"raw_affiliation_string":"School of Mathematical Sciences University of Electronic Science and Technology of China  Chengdu China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022895441"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":3.9019,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.95046732,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"23","issue":"12","first_page":"5470","last_page":"5485"},"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":0.9995999932289124,"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":0.9994999766349792,"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/inpainting","display_name":"Inpainting","score":0.8818373680114746},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.8366529941558838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6010453104972839},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5847448110580444},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5296254754066467},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5021469593048096},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.49247583746910095},{"id":"https://openalex.org/keywords/cascade-algorithm","display_name":"Cascade algorithm","score":0.4913429319858551},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46625933051109314},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4446372985839844},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.41320866346359253},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.41206198930740356},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37151646614074707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.368795245885849},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28015148639678955}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.8818373680114746},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.8366529941558838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6010453104972839},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5847448110580444},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5296254754066467},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5021469593048096},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.49247583746910095},{"id":"https://openalex.org/C88829872","wikidata":"https://www.wikidata.org/wiki/Q5048176","display_name":"Cascade algorithm","level":5,"score":0.4913429319858551},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46625933051109314},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4446372985839844},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.41320866346359253},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.41206198930740356},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37151646614074707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.368795245885849},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28015148639678955},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2014.2362051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2014.2362051","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:25312924","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/25312924","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G4059144","display_name":null,"funder_award_id":"11201054","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6863714809","display_name":null,"funder_award_id":"91330201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7734321245","display_name":null,"funder_award_id":"ZYGX2012J118","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8761711584","display_name":null,"funder_award_id":"ZYGX2013Z005","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W40037269","https://openalex.org/W74071737","https://openalex.org/W136272581","https://openalex.org/W1536341104","https://openalex.org/W1603765807","https://openalex.org/W1973700755","https://openalex.org/W1975260365","https://openalex.org/W1978333359","https://openalex.org/W1978885364","https://openalex.org/W1981624870","https://openalex.org/W1983772857","https://openalex.org/W1992609597","https://openalex.org/W1999905919","https://openalex.org/W2006262045","https://openalex.org/W2016910236","https://openalex.org/W2021535288","https://openalex.org/W2021583769","https://openalex.org/W2023722580","https://openalex.org/W2025263014","https://openalex.org/W2032240925","https://openalex.org/W2039939700","https://openalex.org/W2045079045","https://openalex.org/W2057624533","https://openalex.org/W2058532290","https://openalex.org/W2075506710","https://openalex.org/W2086670019","https://openalex.org/W2091494211","https://openalex.org/W2093834886","https://openalex.org/W2097474301","https://openalex.org/W2097924771","https://openalex.org/W2103559027","https://openalex.org/W2104031318","https://openalex.org/W2107861471","https://openalex.org/W2108454251","https://openalex.org/W2110505738","https://openalex.org/W2111394763","https://openalex.org/W2122315118","https://openalex.org/W2125555749","https://openalex.org/W2127436071","https://openalex.org/W2132122471","https://openalex.org/W2133665775","https://openalex.org/W2142058898","https://openalex.org/W2145003640","https://openalex.org/W2146378240","https://openalex.org/W2146842127","https://openalex.org/W2151554678","https://openalex.org/W2154996879","https://openalex.org/W2156575092","https://openalex.org/W2157434051","https://openalex.org/W2164452299","https://openalex.org/W2166956514","https://openalex.org/W2168745297","https://openalex.org/W2296616510","https://openalex.org/W2322609174","https://openalex.org/W2623831436","https://openalex.org/W2762625016","https://openalex.org/W2963347434","https://openalex.org/W3012080241","https://openalex.org/W3124114587","https://openalex.org/W4250955649","https://openalex.org/W4255272544","https://openalex.org/W4285719527","https://openalex.org/W4301283118","https://openalex.org/W6674737082","https://openalex.org/W6684416548","https://openalex.org/W6684677280","https://openalex.org/W6738668529","https://openalex.org/W6775638715"],"related_works":["https://openalex.org/W2144834862","https://openalex.org/W2054017055","https://openalex.org/W1588899229","https://openalex.org/W4321517526","https://openalex.org/W1976022598","https://openalex.org/W2111896212","https://openalex.org/W1967182499","https://openalex.org/W2097034666","https://openalex.org/W2085792030","https://openalex.org/W2391053410"],"abstract_inverted_index":{"The":[0,73],"wavelet":[1,24,40,59,100,120,143,168,216],"frame":[2,41,101,121,144,217],"systems":[3],"have":[4],"been":[5],"extensively":[6],"studied":[7],"due":[8,204],"to":[9,123,161,205,208],"their":[10,206],"capability":[11],"of":[12,35,39,79,104,113,118,137,141,198,201,211,214],"sparsely":[13],"approximating":[14],"piece-wise":[15],"smooth":[16],"functions,":[17],"such":[18,189],"as":[19,134,175,177,190],"images,":[20],"and":[21,67,88,94,107],"the":[22,33,36,52,58,77,95,114,119,125,135,142,147,156,162,212,215],"corresponding":[23,70],"frame-based":[25,169],"image":[26,53,105,172],"restoration":[27,65],"models":[28],"are":[29],"mostly":[30],"based":[31,56],"on":[32,51,57],"penalization":[34],"l1":[37,102,149,170],"norm":[38,171],"coefficients":[42,122,145],"for":[43,90,99,167],"sparsity":[44],"enforcement.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49],"focus":[50],"inpainting":[54,173],"problem":[55],"frame,":[60],"propose":[61],"a":[62,69],"weighted":[63],"sparse":[64,91],"model,":[66],"develop":[68],"efficient":[71],"algorithm.":[72],"new":[74,129],"algorithm":[75,130],"combines":[76],"idea":[78],"iterative":[80],"support":[81],"detection":[82],"method,":[83,195],"first":[84],"proposed":[85,157],"by":[86],"Wang":[87],"Yin":[89],"signal":[92],"reconstruction,":[93],"split":[96,164],"Bregman":[97,165],"method":[98,158,166],"model":[103,174],"inpainting,":[106],"more":[108],"important,":[109],"naturally":[110],"makes":[111],"use":[112,210],"specific":[115],"multilevel":[116],"structure":[117,213],"enhance":[124],"recovery":[126],"quality.":[127],"This":[128],"can":[131],"be":[132],"considered":[133],"incorporation":[136],"prior":[138],"structural":[139],"information":[140],"into":[146],"traditional":[148],"model.":[150],"Our":[151],"numerical":[152],"experiments":[153],"show":[154],"that":[155],"is":[159],"superior":[160],"original":[163],"well":[176],"some":[178],"typical":[179],"l(p)":[180],"(0":[181],"\u2264":[182],"p":[183],"<":[184],"1)":[185],"norm-based":[186],"nonconvex":[187],"algorithms":[188],"mean":[191],"doubly":[192],"augmented":[193],"Lagrangian":[194],"in":[196],"terms":[197],"better":[199],"preservation":[200],"sharp":[202],"edges,":[203],"failing":[207],"make":[209],"coefficients.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-02-19T06:27:42.648592","created_date":"2025-10-10T00:00:00"}
