{"id":"https://openalex.org/W2771296580","doi":"https://doi.org/10.1109/access.2017.2778947","title":"Hyperspectral Image Denoising With Group Sparse and Low-Rank Tensor Decomposition","display_name":"Hyperspectral Image Denoising With Group Sparse and Low-Rank Tensor Decomposition","publication_year":2017,"publication_date":"2017-11-30","ids":{"openalex":"https://openalex.org/W2771296580","doi":"https://doi.org/10.1109/access.2017.2778947","mag":"2771296580"},"language":"en","primary_location":{"id":"doi:10.1109/access.2017.2778947","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2778947","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2017.2778947","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063874284","display_name":"Zhihong Huang","orcid":"https://orcid.org/0000-0003-0549-1059"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Huang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065061505","display_name":"Leyuan Fang","orcid":"https://orcid.org/0000-0003-2351-4461"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyuan Fang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100757121","display_name":"Huali Li","orcid":"https://orcid.org/0000-0003-2210-2780"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huali Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-2210-2780","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035508615","display_name":"J\u00f3n Atli Benediktsson","orcid":"https://orcid.org/0000-0003-0621-9647"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Jon Atli Benediktsson","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland"],"raw_orcid":"https://orcid.org/0000-0003-0621-9647","affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":2.2768,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.9216145,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"1380","last_page":"1390"},"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":0.9997000098228455,"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":0.998199999332428,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7057402729988098},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6140041947364807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6018888354301453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5629038214683533},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5437170267105103},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5405775904655457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5290464758872986},{"id":"https://openalex.org/keywords/tensor-decomposition","display_name":"Tensor decomposition","score":0.46656882762908936},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4623616337776184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.459879070520401},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4456174075603485},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.4455646276473999},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43468111753463745},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4282049238681793},{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.42411521077156067},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3455740213394165},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3210875391960144},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2789944112300873},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.15875732898712158},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1254170536994934}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7057402729988098},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6140041947364807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6018888354301453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5629038214683533},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5437170267105103},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5405775904655457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5290464758872986},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.46656882762908936},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4623616337776184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.459879070520401},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4456174075603485},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.4455646276473999},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43468111753463745},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4282049238681793},{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.42411521077156067},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3455740213394165},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3210875391960144},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2789944112300873},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.15875732898712158},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1254170536994934},{"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2017.2778947","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2778947","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7188496a5cef4938b57bead5c5376364","is_oa":true,"landing_page_url":"https://doaj.org/article/7188496a5cef4938b57bead5c5376364","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 1380-1390 (2018)","raw_type":"article"},{"id":"pmh:oai:opinvisindi.is:20.500.11815/821","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.11815/821","pdf_url":null,"source":{"id":"https://openalex.org/S4306401866","display_name":"Opin v\u00edsindi (Opin v\u00edsindi)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/access.2017.2778947","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2017.2778947","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1904756914","display_name":null,"funder_award_id":"61301255","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3499042801","display_name":"\u590d\u6742\u573a\u666f\u4e2d\u9ad8\u7ef4\u66f2\u7ebf\u7684Hough\u53d8\u6362\u68c0\u6d4b\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61471167","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3693646142","display_name":"\u57fa\u4e8eOCT\u56fe\u50cf\u591a\u75c5\u53d8\u5206\u6790\u7684\u89c6\u7f51\u819c\u75be\u75c5\u81ea\u52a8\u8bca\u65ad\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61771192","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320332375","display_name":"Jet Propulsion Laboratory","ror":"https://ror.org/027k65916"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1671163461","https://openalex.org/W1944540851","https://openalex.org/W1969352102","https://openalex.org/W1974438823","https://openalex.org/W1994040806","https://openalex.org/W2024165284","https://openalex.org/W2030927653","https://openalex.org/W2038590919","https://openalex.org/W2039596145","https://openalex.org/W2052160904","https://openalex.org/W2056370875","https://openalex.org/W2067983477","https://openalex.org/W2073459066","https://openalex.org/W2125298866","https://openalex.org/W2129891925","https://openalex.org/W2134179406","https://openalex.org/W2145962650","https://openalex.org/W2146344928","https://openalex.org/W2148717137","https://openalex.org/W2155124307","https://openalex.org/W2165141499","https://openalex.org/W2165329055","https://openalex.org/W2298855392","https://openalex.org/W2329868263","https://openalex.org/W2480706550","https://openalex.org/W2557395112","https://openalex.org/W2589095374","https://openalex.org/W2591248827","https://openalex.org/W2595902385","https://openalex.org/W2606327983","https://openalex.org/W2617818785","https://openalex.org/W2735711969","https://openalex.org/W2964214749","https://openalex.org/W4285719527","https://openalex.org/W6668990524"],"related_works":["https://openalex.org/W3213449325","https://openalex.org/W4391266752","https://openalex.org/W2898722594","https://openalex.org/W2125326641","https://openalex.org/W123932431","https://openalex.org/W2897430141","https://openalex.org/W2091381096","https://openalex.org/W2514994112","https://openalex.org/W2735711969","https://openalex.org/W4210620599"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"is":[3,71,122,174],"usually":[4],"corrupted":[5],"by":[6,139,157],"various":[7],"types":[8],"of":[9,48,77,128,165,208],"noise,":[10,13,15],"including":[11],"Gaussian":[12],"impulse":[14],"stripes,":[16],"deadlines,":[17],"and":[18,23,50,65,86,114,167,200],"so":[19],"on.":[20],"Recently,":[21],"sparse":[22,64,113],"low-rank":[24,66,115],"matrix":[25],"decomposition":[26,68,117],"(SLRMD)":[27],"has":[28],"demonstrated":[29],"to":[30,73,176],"be":[31,96,151],"an":[32],"effective":[33],"tool":[34],"in":[35,53,79],"HSI":[36,56,93,108,121,202],"denoising.":[37],"However,":[38],"the":[39,46,102,120,171,206,209],"matrix-based":[40],"SLRMD":[41],"technique":[42],"cannot":[43],"fully":[44],"take":[45],"advantage":[47],"spatial":[49,87],"spectral":[51,85],"information":[52],"a":[54,61,90,99,107,112,126,154,163,193],"3-D":[55,92,100,130],"data.":[57],"In":[58],"this":[59],"paper,":[60],"novel":[62],"group":[63,144,182,188],"tensor":[67,116,131,147,156],"(GSLRTD)":[69],"method":[70,105],"proposed":[72,103,210],"remove":[74],"different":[75],"kinds":[76],"noise":[78],"HSI,":[80],"while":[81],"still":[82],"well":[83],"preserving":[84],"characteristics.":[88],"Since":[89],"clean":[91],"data":[94,203],"can":[95,150,191],"regarded":[97],"as":[98,153],"tensor,":[101],"GSLRTD":[104],"formulates":[106],"recovery":[109],"problem":[110],"into":[111,125,137,162],"framework.":[118],"Specifically,":[119],"first":[123],"divided":[124],"set":[127,164],"overlapping":[129],"cubes,":[132,148],"which":[133,149],"are":[134],"then":[135],"clustered":[136],"groups":[138],"K-means":[140],"algorithm.":[141],"Then,":[142],"each":[143,181],"contains":[145],"similar":[146,160],"constructed":[152],"new":[155],"unfolding":[158],"these":[159],"tensors":[161],"matrices":[166],"stacking":[168],"them.":[169],"Finally,":[170],"SLRTD":[172],"model":[173],"introduced":[175],"generate":[177],"noisefree":[178],"estimation":[179],"for":[180],"tensor.":[183],"By":[184],"aggregating":[185],"all":[186],"reconstructed":[187],"tensors,":[189],"we":[190],"reconstruct":[192],"denoised":[194],"HSI.":[195],"Experiments":[196],"on":[197],"both":[198],"simulated":[199],"real":[201],"sets":[204],"demonstrate":[205],"effectiveness":[207],"method.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":4}],"updated_date":"2026-08-22T07:34:49.880490","created_date":"2025-10-10T00:00:00"}