{"id":"https://openalex.org/W3131584695","doi":"https://doi.org/10.1109/igarss39084.2020.9323403","title":"Hyperspectral Image Restoration via Global Total Variation Regularized Local Nonconvex Low-Rank Matrix Approximation","display_name":"Hyperspectral Image Restoration via Global Total Variation Regularized Local Nonconvex Low-Rank Matrix Approximation","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3131584695","doi":"https://doi.org/10.1109/igarss39084.2020.9323403","mag":"3131584695"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9323403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5020975557","display_name":"Haijin Zeng","orcid":"https://orcid.org/0000-0003-0398-3316"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haijin Zeng","raw_affiliation_strings":["Northwest A&F University, College of Science, Yangling, P.R. China"],"affiliations":[{"raw_affiliation_string":"Northwest A&F University, College of Science, Yangling, P.R. China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075409203","display_name":"Xiaozhen Xie","orcid":"https://orcid.org/0000-0003-3715-0777"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaozhen Xie","raw_affiliation_strings":["Northwest A&F University, College of Science, Yangling, P.R. China"],"affiliations":[{"raw_affiliation_string":"Northwest A&F University, College of Science, Yangling, P.R. China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037531369","display_name":"Jifeng Ning","orcid":"https://orcid.org/0000-0002-7751-0936"},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jifeng Ning","raw_affiliation_strings":["Northwest A&F University, College of Science, Yangling, P.R. China"],"affiliations":[{"raw_affiliation_string":"Northwest A&F University, College of Science, Yangling, P.R. China","institution_ids":["https://openalex.org/I89652312"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5020975557"],"corresponding_institution_ids":["https://openalex.org/I89652312"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.32428239,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"11","issue":null,"first_page":"2312","last_page":"2315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9994999766349792,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9986000061035156,"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/low-rank-approximation","display_name":"Low-rank approximation","score":0.6233784556388855},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.6186233758926392},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5996735692024231},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5947908163070679},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5901920795440674},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.5180218815803528},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4858086109161377},{"id":"https://openalex.org/keywords/matrix-completion","display_name":"Matrix completion","score":0.47304385900497437},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47236090898513794},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.4343968629837036},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4201650619506836},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.41913890838623047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35783660411834717},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.32466432452201843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21395832300186157},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.18737155199050903},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.16581621766090393},{"id":"https://openalex.org/keywords/hankel-matrix","display_name":"Hankel matrix","score":0.1267484724521637},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09658446907997131},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09591361880302429}],"concepts":[{"id":"https://openalex.org/C90199385","wikidata":"https://www.wikidata.org/wiki/Q6692777","display_name":"Low-rank approximation","level":3,"score":0.6233784556388855},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.6186233758926392},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5996735692024231},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5947908163070679},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5901920795440674},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.5180218815803528},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4858086109161377},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.47304385900497437},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47236090898513794},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.4343968629837036},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4201650619506836},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.41913890838623047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35783660411834717},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.32466432452201843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21395832300186157},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.18737155199050903},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.16581621766090393},{"id":"https://openalex.org/C25023664","wikidata":"https://www.wikidata.org/wiki/Q1575637","display_name":"Hankel matrix","level":2,"score":0.1267484724521637},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09658446907997131},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09591361880302429},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss39084.2020.9323403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9323403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"},{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G3937131714","display_name":null,"funder_award_id":"2452019073","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8257642396","display_name":null,"funder_award_id":"61876153","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1634387560","https://openalex.org/W1944540851","https://openalex.org/W1991003630","https://openalex.org/W1994040806","https://openalex.org/W2056370875","https://openalex.org/W2066986830","https://openalex.org/W2146130798","https://openalex.org/W2724686744","https://openalex.org/W3003365835","https://openalex.org/W3103820806","https://openalex.org/W4285719527","https://openalex.org/W6682042988"],"related_works":["https://openalex.org/W2964006653","https://openalex.org/W2788826952","https://openalex.org/W2084983808","https://openalex.org/W1991825408","https://openalex.org/W4318564253","https://openalex.org/W4302315572","https://openalex.org/W1969698720","https://openalex.org/W1507830821","https://openalex.org/W2325477568","https://openalex.org/W2184500224"],"abstract_inverted_index":{"Several":[0],"bandwise":[1,69,175],"total":[2],"variation":[3],"(TV)":[4],"regularized":[5,91],"low-rank":[6],"(LR)-based":[7],"models":[8],"have":[9],"been":[10],"proposed":[11],"to":[12,99,123,137,182],"remove":[13,100],"mixed":[14,101],"noise":[15,102],"in":[16,53,76,103,141,151],"hyperspectral":[17],"images":[18],"(HSIs).":[19],"Conventionally,":[20],"the":[21,48,59,73,124,128,142,153,162,165,172,179,198,209],"rank":[22,126],"of":[23,47,110,164,174,191,200,211],"LR":[24,94,109],"matrix":[25,61,95,125],"is":[26,34,43,112,149],"approximated":[27],"using":[28,114],"nuclear":[29],"norm":[30],"(NN).":[31],"The":[32,146],"NN":[33],"defined":[35],"by":[36],"adding":[37],"all":[38],"singular":[39,49],"values":[40],"together,":[41],"which":[42,118],"essentially":[44],"a":[45,77,87,115,120],"L1-norm":[46],"values.":[50],"It":[51],"results":[52,195],"non-negligible":[54],"approximation":[55,96,122],"errors":[56],"and":[57,155,188,204,215],"thus":[58],"resulting":[60],"estimator":[62],"can":[63,207],"be":[64,138],"significantly":[65],"biased.":[66],"Moreover,":[67],"these":[68,83],"TV-based":[70],"methods":[71],"exploit":[72],"spatial":[74,144,186,212],"information":[75],"separate":[78],"manner.":[79],"To":[80,170],"cope":[81],"with":[82,167],"problems,":[84],"we":[85,177],"propose":[86],"spatial-spectral":[88],"TV":[89,147,168],"(SSTV)":[90],"non-convex":[92,116,202],"local":[93,108,201],"(NonLLRTV)":[97],"method":[98],"HSIs.":[104],"From":[105,131],"one":[106],"aspect,":[107,133],"HSIs":[111,134],"formulated":[113],"L\u03b3-norm,":[117],"provides":[119],"closer":[121],"than":[127],"traditional":[129],"NN.":[130],"another":[132],"are":[135],"assumed":[136],"piecewisely":[139],"smooth":[140],"global":[143,185,205],"domain.":[145],"regularization":[148,181],"effective":[150],"preserving":[152,210],"smoothness":[154,214],"removing":[156],"Gaussian":[157],"noise.":[158],"These":[159],"facts":[160],"inspire":[161],"integration":[163],"NonLLR":[166],"regularization.":[169],"address":[171],"limitations":[173],"TV,":[176],"use":[178,199],"SSTV":[180,206],"simultaneously":[183],"consider":[184],"structure":[187],"spectral":[189],"correlation":[190],"neighboring":[192],"bands.":[193],"Experiment":[194],"indicate":[196],"that":[197],"penalty":[203],"boost":[208],"piecewise":[213],"overall":[216],"structural":[217],"information.":[218]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}