{"id":"https://openalex.org/W4399618239","doi":"https://doi.org/10.1109/tcsvt.2024.3413992","title":"Robust Tensor Completion via Dictionary Learning and Generalized Nonconvex Regularization for Visual Data Recovery","display_name":"Robust Tensor Completion via Dictionary Learning and Generalized Nonconvex Regularization for Visual Data Recovery","publication_year":2024,"publication_date":"2024-06-13","ids":{"openalex":"https://openalex.org/W4399618239","doi":"https://doi.org/10.1109/tcsvt.2024.3413992"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2024.3413992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2024.3413992","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","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/A5030009104","display_name":"Duo Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Duo Qiu","raw_affiliation_strings":["School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072642143","display_name":"Bei Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bei Yang","raw_affiliation_strings":["School of Mathematics and Statistics, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072740546","display_name":"Xiongjun Zhang","orcid":"https://orcid.org/0000-0002-5387-4129"},"institutions":[{"id":"https://openalex.org/I40963666","display_name":"Central China Normal University","ror":"https://ror.org/03x1jna21","country_code":"CN","type":"education","lineage":["https://openalex.org/I40963666"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiongjun Zhang","raw_affiliation_strings":["School of Mathematics and Statistics and Hubei Key Laboratory of Mathematical Sciences, Central China Normal University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics and Hubei Key Laboratory of Mathematical Sciences, Central China Normal University, Wuhan, China","institution_ids":["https://openalex.org/I40963666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5030009104"],"corresponding_institution_ids":["https://openalex.org/I91125648"],"apc_list":null,"apc_paid":null,"fwci":2.9355,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.92200642,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"34","issue":"11","first_page":"11026","last_page":"11039"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9965999722480774,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9965999722480774,"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":0.9965999722480774,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9955000281333923,"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/computer-science","display_name":"Computer science","score":0.5324804782867432},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5050502419471741},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48577550053596497},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.45506617426872253},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.390097975730896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36086201667785645},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3317905068397522},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.21369606256484985}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5324804782867432},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5050502419471741},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48577550053596497},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.45506617426872253},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.390097975730896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36086201667785645},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3317905068397522},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.21369606256484985}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2024.3413992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2024.3413992","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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 Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4132392344","display_name":null,"funder_award_id":"CCNU24JC004","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G414549944","display_name":null,"funder_award_id":"12171189","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6168379195","display_name":null,"funder_award_id":"12201473","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/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/W1568416770","https://openalex.org/W1890834058","https://openalex.org/W1963826206","https://openalex.org/W1965125844","https://openalex.org/W1966661320","https://openalex.org/W1967138577","https://openalex.org/W1975900269","https://openalex.org/W1993482030","https://openalex.org/W1999136078","https://openalex.org/W1999829977","https://openalex.org/W2000015923","https://openalex.org/W2020925091","https://openalex.org/W2024165284","https://openalex.org/W2027982384","https://openalex.org/W2038891887","https://openalex.org/W2043571470","https://openalex.org/W2074682976","https://openalex.org/W2079705627","https://openalex.org/W2091449379","https://openalex.org/W2103559027","https://openalex.org/W2118550318","https://openalex.org/W2133665775","https://openalex.org/W2139208832","https://openalex.org/W2161305109","https://openalex.org/W2218665234","https://openalex.org/W2258054274","https://openalex.org/W2412278696","https://openalex.org/W2757057438","https://openalex.org/W2883289611","https://openalex.org/W2896928944","https://openalex.org/W2901836533","https://openalex.org/W2918050465","https://openalex.org/W2954249638","https://openalex.org/W2962708900","https://openalex.org/W2963328634","https://openalex.org/W2963885538","https://openalex.org/W2966520830","https://openalex.org/W2979001238","https://openalex.org/W3011789951","https://openalex.org/W3038214644","https://openalex.org/W3045398543","https://openalex.org/W3087302085","https://openalex.org/W3115008168","https://openalex.org/W3120121719","https://openalex.org/W3120378560","https://openalex.org/W3123648408","https://openalex.org/W3132491426","https://openalex.org/W3133825763","https://openalex.org/W3133941073","https://openalex.org/W3198865231","https://openalex.org/W3200346087","https://openalex.org/W3205098874","https://openalex.org/W4205793477","https://openalex.org/W4206319168","https://openalex.org/W4225816429","https://openalex.org/W4281401255","https://openalex.org/W4297962080","https://openalex.org/W4361295184","https://openalex.org/W4362474484","https://openalex.org/W4379528713","https://openalex.org/W4379599270","https://openalex.org/W4380607122","https://openalex.org/W4385553849","https://openalex.org/W4386648952","https://openalex.org/W4386824702","https://openalex.org/W6675666277","https://openalex.org/W6682433143","https://openalex.org/W6717575008"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2053286651","https://openalex.org/W2181743346","https://openalex.org/W2187401768","https://openalex.org/W2181413294","https://openalex.org/W2989452537","https://openalex.org/W2052122378","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Robust":[0],"tensor":[1,8,43,58,82,118,136,160],"completion,":[2],"which":[3,46,153],"aims":[4],"to":[5,64,128,177],"recover":[6],"a":[7,21,77,100,139],"from":[9],"partial":[10],"observations":[11],"corrupted":[12],"by":[13,84],"Gaussian":[14],"noise":[15,18],"and":[16,68,89,197],"sparse":[17,151],"simultaneously,":[19,71],"has":[20],"wide":[22],"range":[23],"of":[24,35,55,95,102,111,115,133,141,149],"applications":[25],"in":[26,72,119],"visual":[27],"data":[28,59],"recovery.":[29],"The":[30,123],"existing":[31],"approaches":[32],"make":[33],"use":[34],"convex":[36],"or":[37],"nonconvex":[38,78,90,103,142],"relaxation":[39],"based":[40],"on":[41,193],"transformed":[42,121],"nuclear":[44],"norm,":[45],"may":[47],"be":[48],"challenged":[49],"since":[50],"only":[51],"the":[52,56,66,86,93,97,108,116,120,130,134,150,179,204],"global":[53,67,98],"low-rankness":[54],"underlying":[57,117,135],"is":[60,126,175,184],"utilized.":[61],"In":[62],"order":[63],"explore":[65],"local":[69,131],"patterns":[70,132],"this":[73],"paper,":[74],"we":[75],"propose":[76],"model":[79,206],"for":[80],"robust":[81],"completion":[83],"combining":[85],"dictionary":[87,124],"learning":[88,125],"regularization.":[91],"For":[92],"sake":[94],"exploring":[96],"low-rankness,":[99],"family":[101,140],"functions":[104,143],"are":[105,144],"employed":[106],"onto":[107,146],"singular":[109],"values":[110],"all":[112],"frontal":[113],"slices":[114],"domain.":[122],"utilized":[127],"elucidate":[129],"data.":[137],"Moreover,":[138],"used":[145],"each":[147],"entry":[148],"noise,":[152],"can":[154],"obtain":[155],"sparser":[156],"solutions":[157],"compared":[158],"with":[159],"<inline-formula":[161],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[162],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[163],"<tex-math":[164],"notation=\"LaTeX\">$\\ell":[165],"_{1}$":[166],"</tex-math></inline-formula>":[167],"norm.":[168],"A":[169],"proximal":[170],"alternating":[171],"linearized":[172],"minimization":[173],"algorithm":[174],"designed":[176],"solve":[178],"proposed":[180,205],"model,":[181],"whose":[182],"convergence":[183],"established":[185],"under":[186],"very":[187],"mild":[188],"conditions.":[189],"Extensive":[190],"numerical":[191],"experiments":[192],"multispectral":[194],"images,":[195],"video,":[196],"magnetic":[198],"resonance":[199],"imaging":[200],"datasets":[201],"show":[202],"that":[203],"outperforms":[207],"other":[208],"state-of-the-art":[209],"approaches.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}