{"id":"https://openalex.org/W3130779229","doi":"https://doi.org/10.1109/jstsp.2021.3058503","title":"Tensor Low-Rank Constraint and $l_0$ Total Variation for Hyperspectral Image Mixed Noise Removal","display_name":"Tensor Low-Rank Constraint and $l_0$ Total Variation for Hyperspectral Image Mixed Noise Removal","publication_year":2021,"publication_date":"2021-02-13","ids":{"openalex":"https://openalex.org/W3130779229","doi":"https://doi.org/10.1109/jstsp.2021.3058503","mag":"3130779229"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2021.3058503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3058503","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","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/A5100325515","display_name":"Minghua Wang","orcid":"https://orcid.org/0000-0001-5715-130X"},"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":true,"raw_author_name":"Minghua Wang","raw_affiliation_strings":["Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","HIT - Harbin Institute of Technology (92 West Dazhi Street , Nan Gang District, Harbin\r\nPost Code: 150001 - China)"],"affiliations":[{"raw_affiliation_string":"Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"HIT - Harbin Institute of Technology (92 West Dazhi Street , Nan Gang District, Harbin\r\nPost Code: 150001 - China)","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055119440","display_name":"Qiang Wang","orcid":"https://orcid.org/0000-0002-9654-0268"},"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":"Qiang Wang","raw_affiliation_strings":["Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","HIT - Harbin Institute of Technology (92 West Dazhi Street , Nan Gang District, Harbin\r\nPost Code: 150001 - China)"],"affiliations":[{"raw_affiliation_string":"Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"HIT - Harbin Institute of Technology (92 West Dazhi Street , Nan Gang District, Harbin\r\nPost Code: 150001 - China)","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210101348","display_name":"Centre Inria de l'Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/00n8d6z93","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1326498283","https://openalex.org/I4210101348"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210149092","display_name":"Laboratoire Jean Kuntzmann","ror":"https://ror.org/04ett5b41","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I4210149092","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["CN","FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["Chinese Academy of Sciences, Aerospace Information research Institute, Beijing, China","University Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, France","GIPSA-SIGMAPHY - GIPSA - Signal Images Physique (GIPSA-lab, 11 rue des Math\u00e9matiques, Grenoble Campus BP46, F-38402 SAINT MARTIN D'HERES CEDEX - France)","Thoth - Apprentissage de mod\u00e8les \u00e0 partir de donn\u00e9es massives (France)"],"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences, Aerospace Information research Institute, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210149092","https://openalex.org/I4210101348","https://openalex.org/I899635006","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"GIPSA-SIGMAPHY - GIPSA - Signal Images Physique (GIPSA-lab, 11 rue des Math\u00e9matiques, Grenoble Campus BP46, F-38402 SAINT MARTIN D'HERES CEDEX - France)","institution_ids":["https://openalex.org/I4210124956"]},{"raw_affiliation_string":"Thoth - Apprentissage de mod\u00e8les \u00e0 partir de donn\u00e9es massives (France)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100325515"],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":4.5539,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.95823609,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"15","issue":"3","first_page":"718","last_page":"733"},"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":0.9995999932289124,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9993000030517578,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5636587142944336},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5574427843093872},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5266739726066589},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4885774552822113},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.48597490787506104},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4697309732437134},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.459457665681839},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4423431158065796},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4227052330970764},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37868839502334595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3646790087223053},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36038047075271606},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.26278936862945557}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5636587142944336},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5574427843093872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5266739726066589},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4885774552822113},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.48597490787506104},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4697309732437134},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.459457665681839},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4423431158065796},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4227052330970764},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37868839502334595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3646790087223053},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36038047075271606},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.26278936862945557},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstsp.2021.3058503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3058503","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-03429632v1","is_oa":false,"landing_page_url":"https://hal.science/hal-03429632","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Signal Processing, 2021, 15 (3), pp.718-733. &#x27E8;10.1109/JSTSP.2021.3058503&#x27E9;","raw_type":"Journal articles"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3047845980","display_name":null,"funder_award_id":"61876054","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/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1736339626","https://openalex.org/W1944540851","https://openalex.org/W1985242206","https://openalex.org/W1991003630","https://openalex.org/W1994040806","https://openalex.org/W2024165284","https://openalex.org/W2030927653","https://openalex.org/W2039596145","https://openalex.org/W2047705660","https://openalex.org/W2057374579","https://openalex.org/W2061052400","https://openalex.org/W2069889146","https://openalex.org/W2087263574","https://openalex.org/W2091449379","https://openalex.org/W2119993761","https://openalex.org/W2122752532","https://openalex.org/W2136251662","https://openalex.org/W2163232332","https://openalex.org/W2163886442","https://openalex.org/W2163957348","https://openalex.org/W2164278908","https://openalex.org/W2167307343","https://openalex.org/W2171520281","https://openalex.org/W2187214659","https://openalex.org/W2280622051","https://openalex.org/W2289756263","https://openalex.org/W2295652899","https://openalex.org/W2339170012","https://openalex.org/W2401672073","https://openalex.org/W2480706550","https://openalex.org/W2578004414","https://openalex.org/W2608092940","https://openalex.org/W2614611154","https://openalex.org/W2624915162","https://openalex.org/W2724686744","https://openalex.org/W2735711969","https://openalex.org/W2747865121","https://openalex.org/W2773415061","https://openalex.org/W2790528326","https://openalex.org/W2793218933","https://openalex.org/W2805465265","https://openalex.org/W2806155925","https://openalex.org/W2895909348","https://openalex.org/W2897962879","https://openalex.org/W2902746003","https://openalex.org/W2919868964","https://openalex.org/W2944388294","https://openalex.org/W2952565170","https://openalex.org/W2954868192","https://openalex.org/W2962747489","https://openalex.org/W2963213461","https://openalex.org/W2964179170","https://openalex.org/W2964214749","https://openalex.org/W2979442703","https://openalex.org/W2980079746","https://openalex.org/W2992775778","https://openalex.org/W2998656915","https://openalex.org/W3022425365","https://openalex.org/W3032341357","https://openalex.org/W3040988483","https://openalex.org/W3046027728","https://openalex.org/W3098435832","https://openalex.org/W3100203369","https://openalex.org/W3101501663","https://openalex.org/W3103919952","https://openalex.org/W3105393233","https://openalex.org/W3122774149","https://openalex.org/W3129376454","https://openalex.org/W3131515870","https://openalex.org/W3180153763","https://openalex.org/W4292363360","https://openalex.org/W6798144013","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3034864990"],"abstract_inverted_index":{"Several":[0],"methods":[1,21],"based":[2],"on":[3,39,120],"Total":[4,59,95],"Variation":[5,60,96],"(TV)":[6],"have":[7],"been":[8],"proposed":[9,225,248],"for":[10,71,81,135],"Hyperspectral":[11],"Image":[12],"(HSI)":[13],"denoising.":[14,145],"However,":[15],"the":[16,40,72,113,122,141,147,156,194,203,224,247],"TV":[17,110,179,208,215,253],"terms":[18],"of":[19,42,115,150,159,190,234],"these":[20],"just":[22],"use":[23],"various":[24],"l":[25,55,91,106,204],"<sub":[26,56,62,92,98,107,169,176,182,205,212,250],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[27,57,63,93,99,108,170,177,183,206,213,251],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[28],"norms":[29],"and":[30,45,69,90,118,155,180,193,210,221],"penalize":[31],"image":[32,124],"gradient":[33],"magnitudes,":[34],"having":[35],"a":[36,53,85],"negative":[37],"influence":[38],"preprocessing":[41],"HSI":[43,47,73,237],"denoising":[44,245],"further":[46],"classification":[48,143,238],"task.":[49],"In":[50,218],"this":[51,104],"paper,":[52],"novel":[54,86],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">0</sub>":[58,64,94,100,109,171,178,184,207,214,252],"(l":[61],"TV)":[65,101],"is":[66,132,240],"first":[67],"introduced":[68],"analyzed":[70],"noise":[74,232],"removal":[75,233],"framework":[76],"to":[77,201],"preserve":[78],"more":[79,242],"information":[80,128],"classification.":[82],"We":[83],"propose":[84,166],"Tensor":[87,161],"low-rank":[88],"constraint":[89],"(TLR-l":[97],"model":[102,209],"in":[103,230],"paper.":[105],"directly":[111],"controls":[112],"number":[114],"non-zero":[116],"gradients":[117],"focuses":[119],"recovering":[121],"sharp":[123],"edges.":[125],"The":[126,186],"spectral-spatial":[127],"among":[129],"all":[130],"bands":[131],"exploited":[133],"uniformly":[134],"removing":[136],"mixed":[137,231],"noise,":[138],"which":[139],"facilitates":[140],"subsequent":[142],"after":[144,244],"Including":[146],"Weighted":[148,151,157,160],"Sum":[149,158],"Nuclear":[152,162],"Norm":[153,163],"(WSWNN)":[154],"(WSWTNN),":[164],"we":[165],"two":[167],"TLR-l":[168,211,249],"TV-based":[172],"algorithms,":[173],"namely":[174],"WSWNN-l":[175],"WSWTNN-l":[181],"TV.":[185],"Alternating":[187],"Direction":[188],"Method":[189],"Multipliers":[191],"(ADMM)":[192],"Augmented":[195],"Lagrange":[196],"Multiplier":[197],"(ALM)":[198],"are":[199],"employed":[200],"solve":[202],"model,":[216],"respectively.":[217],"both":[219],"simulated":[220],"real":[222],"data,":[223],"models":[226],"achieve":[227],"superior":[228],"performances":[229],"HSI.":[235],"Especially,":[236],"accuracy":[239],"improved":[241],"effectively":[243],"by":[246],"method.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
