{"id":"https://openalex.org/W2959148625","doi":"https://doi.org/10.1109/tip.2019.2926736","title":"Hyperspectral Images Denoising via Nonconvex Regularized Low-Rank and Sparse Matrix Decomposition","display_name":"Hyperspectral Images Denoising via Nonconvex Regularized Low-Rank and Sparse Matrix Decomposition","publication_year":2019,"publication_date":"2019-07-12","ids":{"openalex":"https://openalex.org/W2959148625","doi":"https://doi.org/10.1109/tip.2019.2926736","mag":"2959148625","pmid":"https://pubmed.ncbi.nlm.nih.gov/31329555"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2926736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2926736","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/A5101773688","display_name":"Ting Xie","orcid":"https://orcid.org/0000-0002-0243-3112"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ting Xie","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100641761","display_name":"Bin Sun","orcid":"https://orcid.org/0000-0002-7029-8784"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Sun","raw_affiliation_strings":["Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Changsha, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101773688"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.9599,"has_fulltext":false,"cited_by_count":92,"citation_normalized_percentile":{"value":0.96212702,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"29","issue":null,"first_page":"44","last_page":"56"},"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":0.9984999895095825,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8817983269691467},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6136400103569031},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5765941143035889},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5764383673667908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.575660228729248},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5661975145339966},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.4987938404083252},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.48212599754333496},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.46839356422424316},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4565422832965851},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4292141795158386},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42604079842567444},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.4126288592815399},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3356568217277527}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8817983269691467},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6136400103569031},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5765941143035889},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5764383673667908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.575660228729248},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5661975145339966},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.4987938404083252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.48212599754333496},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.46839356422424316},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4565422832965851},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4292141795158386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42604079842567444},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.4126288592815399},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3356568217277527},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2019.2926736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2926736","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:31329555","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31329555","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":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G898426514","display_name":null,"funder_award_id":"61520106001","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1799946925","https://openalex.org/W1928626817","https://openalex.org/W1944540851","https://openalex.org/W1965125844","https://openalex.org/W1974438823","https://openalex.org/W1985242206","https://openalex.org/W1991003630","https://openalex.org/W1994040806","https://openalex.org/W1998595580","https://openalex.org/W2009276301","https://openalex.org/W2014311222","https://openalex.org/W2016378714","https://openalex.org/W2039596145","https://openalex.org/W2045983409","https://openalex.org/W2050630265","https://openalex.org/W2053514113","https://openalex.org/W2056370875","https://openalex.org/W2097073572","https://openalex.org/W2129891925","https://openalex.org/W2131628350","https://openalex.org/W2142077116","https://openalex.org/W2145962650","https://openalex.org/W2153295338","https://openalex.org/W2153663612","https://openalex.org/W2155124307","https://openalex.org/W2158400785","https://openalex.org/W2160484748","https://openalex.org/W2161073299","https://openalex.org/W2166229804","https://openalex.org/W2289756263","https://openalex.org/W2336406062","https://openalex.org/W2343117455","https://openalex.org/W2409839127","https://openalex.org/W2505029951","https://openalex.org/W2724686744","https://openalex.org/W2775829438","https://openalex.org/W2790528326","https://openalex.org/W2790888198","https://openalex.org/W2793218933","https://openalex.org/W2802440232","https://openalex.org/W2901807228","https://openalex.org/W2962791795","https://openalex.org/W3098306969","https://openalex.org/W6679973066","https://openalex.org/W6681016373","https://openalex.org/W6714532095"],"related_works":["https://openalex.org/W2374021060","https://openalex.org/W2091883426","https://openalex.org/W3173235360","https://openalex.org/W2174948646","https://openalex.org/W2024017047","https://openalex.org/W4318256793","https://openalex.org/W2051410394","https://openalex.org/W2594370889","https://openalex.org/W2620713272","https://openalex.org/W2898722594"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1],"(HSIs)":[2],"are":[3],"often":[4],"degraded":[5,97],"by":[6],"a":[7,57,63,101,110,127],"mixture":[8],"of":[9,12,51,199,213],"various":[10],"types":[11],"noise":[13,27],"during":[14],"the":[15,30,82,96,115,119,124,151,159,165,170,175,184,190,197,211,214],"imaging":[16],"process,":[17],"including":[18],"Gaussian":[19,83],"noise,":[20,22,84,86],"impulse":[21,85],"and":[23,53,67,89,106,123,181,207],"stripes.":[24,90],"Such":[25],"complex":[26],"could":[28],"plague":[29],"subsequent":[31],"HSIs":[32],"processing.":[33],"Generally,":[34],"most":[35],"HSI":[36,76],"denoising":[37],"methods":[38],"formulate":[39],"sparsity":[40,116],"optimization":[41,162],"problems":[42],"with":[43,109,174],"convex":[44],"norm":[45],"constraints,":[46],"which":[47,78,138,188],"over-penalize":[48],"large":[49],"entries":[50],"vectors,":[52],"may":[54],"result":[55],"in":[56,100,117,178,196],"biased":[58],"solution.":[59],"In":[60,144],"this":[61],"paper,":[62],"nonconvex":[64,129,161,171,191],"regularized":[65],"low-rank":[66,105,121],"sparse":[68,107,125],"matrix":[69,102],"decomposition":[70],"(NonRLRS)":[71],"method":[72],"is":[73,136,155],"proposed":[74,215],"for":[75],"denoising,":[77],"can":[79,139],"simultaneously":[80],"remove":[81],"dead":[87],"lines,":[88],"The":[91],"NonRLRS":[92],"aims":[93],"to":[94,157,193],"decompose":[95],"HSI,":[98],"expressed":[99],"form,":[103],"into":[104],"components":[108],"robust":[111],"formulation.":[112],"To":[113],"enhance":[114],"both":[118,205],"intrinsic":[120],"structure":[122],"corruptions,":[126],"novel":[128],"regularizer":[130],"named":[131],"as":[132],"normalized":[133],"\u03b5":[134],"-penalty,":[135],"presented,":[137],"adaptively":[140],"shrink":[141],"each":[142,179],"entry.":[143],"addition,":[145],"an":[146],"effective":[147],"algorithm":[148,167],"based":[149],"on":[150,204],"majorization":[152],"minimization":[153],"(MM)":[154],"developed":[156],"solve":[158],"resulting":[160],"problem.":[163],"Specifically,":[164],"MM":[166],"first":[168],"substitutes":[169],"objective":[172],"function":[173],"surrogate":[176,186],"upper-bound":[177],"iteration,":[180],"then":[182],"minimizes":[183],"constructed":[185],"function,":[187],"enables":[189],"problem":[192],"be":[194],"solved":[195],"framework":[198],"reweighted":[200],"technique.":[201],"Experimental":[202],"results":[203],"simulated":[206],"real":[208],"data":[209],"demonstrate":[210],"effectiveness":[212],"method.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":10}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}