{"id":"https://openalex.org/W3004881180","doi":"https://doi.org/10.1109/tgrs.2020.2967587","title":"Nonlocal Band-Weighted Iterative Spectral Mixture Model for Hyperspectral Imagery Denoising","display_name":"Nonlocal Band-Weighted Iterative Spectral Mixture Model for Hyperspectral Imagery Denoising","publication_year":2020,"publication_date":"2020-02-06","ids":{"openalex":"https://openalex.org/W3004881180","doi":"https://doi.org/10.1109/tgrs.2020.2967587","mag":"3004881180"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.2967587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2967587","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5078200027","display_name":"Longshan Yang","orcid":"https://orcid.org/0000-0002-3509-2123"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longshan Yang","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3509-2123","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034166335","display_name":"Linlin Xu","orcid":"https://orcid.org/0000-0002-3488-5199"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]},{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Linlin Xu","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences, Beijing, China","University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3488-5199","affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026394989","display_name":"Junhuan Peng","orcid":"https://orcid.org/0000-0002-0587-9486"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhuan Peng","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences, Beijing, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065865699","display_name":"Yongze Song","orcid":"https://orcid.org/0000-0003-3420-9622"},"institutions":[{"id":"https://openalex.org/I205640436","display_name":"Curtin University","ror":"https://ror.org/02n415q13","country_code":"AU","type":"education","lineage":["https://openalex.org/I205640436"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yongze Song","raw_affiliation_strings":["School of Design and the Built Environment, Curtin University, Perth, Australia"],"raw_orcid":"https://orcid.org/0000-0003-3420-9622","affiliations":[{"raw_affiliation_string":"School of Design and the Built Environment, Curtin University, Perth, Australia","institution_ids":["https://openalex.org/I205640436"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102920751","display_name":"Alexander Wong","orcid":"https://orcid.org/0000-0001-5729-5899"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alexander Wong","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0001-5729-5899","affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066149942","display_name":"David A. Clausi","orcid":"https://orcid.org/0000-0002-6383-0875"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"David A. Clausi","raw_affiliation_strings":["University of Waterloo, Waterloo, Canada"],"raw_orcid":"https://orcid.org/0000-0002-6383-0875","affiliations":[{"raw_affiliation_string":"University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3833,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.5935671,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"58","issue":"8","first_page":"5588","last_page":"5601"},"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":0.9994999766349792,"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":0.9994000196456909,"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":0.8534116744995117},{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.7051336765289307},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6349945664405823},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.6151716113090515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6096912026405334},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5824815034866333},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5591064691543579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5540331602096558},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5269378423690796},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4688597321510315},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.46184059977531433},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39189720153808594},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35788220167160034},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24721622467041016}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8534116744995117},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.7051336765289307},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6349945664405823},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.6151716113090515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6096912026405334},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5824815034866333},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5591064691543579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5540331602096558},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5269378423690796},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4688597321510315},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.46184059977531433},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39189720153808594},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35788220167160034},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24721622467041016}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2020.2967587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.2967587","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:espace.curtin.edu.au:20.500.11937/77950","is_oa":false,"landing_page_url":"http://hdl.handle.net/20.500.11937/77950","pdf_url":null,"source":{"id":"https://openalex.org/S4306401790","display_name":"eSpace (Curtin University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205640436","host_organization_name":"Curtin University","host_organization_lineage":["https://openalex.org/I205640436"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2112723906","display_name":null,"funder_award_id":"61427802","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2574134513","display_name":"\u591a\u5e74\u51bb\u571f\u70ed\u529b\u7a33\u5b9a\u6027\u5bf9\u6c14\u5019-\u751f\u6001\u73af\u5883-\u5de5\u7a0b\u6d3b\u52a8\u7684\u590d\u5408\u54cd\u5e94\u8fc7\u7a0b\u548c\u673a\u7406","funder_award_id":"41330634","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3292258137","display_name":"\u968f\u673a\u4fe1\u53f7\u975e\u5e73\u7a33\u60c5\u51b5\u4e0b\u7684\u7a7a\u95f4\u6ee4\u6ce2\u4e0e\u63a8\u4f30\u65b9\u6cd5\u7814\u7a76\u53ca\u5176\u5e94\u7528","funder_award_id":"41374016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G486668507","display_name":null,"funder_award_id":"41501410","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7089208991","display_name":"\u57fa\u4e8e\u6df7\u6c8c\u8bef\u5dee\u7406\u8bba\u7684GPS\u7535\u79bb\u5c42\u7efc\u5408\u5206\u6790\u4e0e\u9884\u62a5\u7814\u7a76","funder_award_id":"41104025","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/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W994592074","https://openalex.org/W1963659868","https://openalex.org/W1964315230","https://openalex.org/W1980849288","https://openalex.org/W1985242206","https://openalex.org/W1997164483","https://openalex.org/W2020460649","https://openalex.org/W2026649668","https://openalex.org/W2033849598","https://openalex.org/W2036524212","https://openalex.org/W2038858414","https://openalex.org/W2039596145","https://openalex.org/W2060403006","https://openalex.org/W2068873421","https://openalex.org/W2070262806","https://openalex.org/W2071128523","https://openalex.org/W2083525611","https://openalex.org/W2095906131","https://openalex.org/W2103909010","https://openalex.org/W2136396015","https://openalex.org/W2148169128","https://openalex.org/W2161073299","https://openalex.org/W2162276208","https://openalex.org/W2171520281","https://openalex.org/W2243541618","https://openalex.org/W2258094320","https://openalex.org/W2323362148","https://openalex.org/W2326001709","https://openalex.org/W2521739939","https://openalex.org/W2771296580","https://openalex.org/W2793237446","https://openalex.org/W2889025125","https://openalex.org/W2899885135","https://openalex.org/W2919868964","https://openalex.org/W2935130647","https://openalex.org/W4238805501","https://openalex.org/W6626122873","https://openalex.org/W6701421198"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W3106536224","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W2890371384","https://openalex.org/W2773863718","https://openalex.org/W2315521504","https://openalex.org/W2563324120","https://openalex.org/W2040756827"],"abstract_inverted_index":{"Although":[0],"efficient":[1],"hyperspectral":[2],"image":[3,85],"(HSI)":[4],"denoising":[5,173],"relies":[6],"on":[7,99,135,159],"complete":[8],"and":[9,12,40,82,122,140,162,172],"accurate":[10,107],"description":[11],"modeling":[13],"the":[14,19,32,36,63,71,100,136,141,150,169,179],"spatial-spectral":[15],"signal":[16,72],"in":[17,73,76],"HSI,":[18,30],"current":[20],"approaches":[21],"do":[22],"not":[23],"fully":[24],"account":[25],"for":[26,84,112,127],"key":[27],"characteristics":[28],"of":[29],"i.e.,":[31],"mixed":[33,74],"spectra":[34],"effect,":[35,39],"spatial":[37,93],"nonstationarity":[38],"noise":[41,108,113,120],"variance":[42,114],"heterogeneity":[43,115],"effect.":[44],"To":[45],"address":[46,91],"this":[47,49],"issue,":[48],"article":[50],"presents":[51],"a":[52,118,123,153],"linear":[53],"spectral":[54],"mixture":[55],"model":[56,121],"with":[57,62,183],"nonlocal":[58],"means":[59,143],"constraint":[60],"(LSMM-NLMC),":[61],"following":[64],"advantages.":[65],"First,":[66],"LSMM-NLMC":[67,88,105,181],"can":[68,89],"effectively":[69],"learn":[70],"pixels":[75],"HSI":[77,164],"by":[78,96,110,178],"estimating":[79],"clean":[80],"endmembers":[81],"abundances":[83],"restoration.":[86],"Second,":[87],"efficiently":[90,148],"nonstationary":[92],"correlation":[94],"effect":[95,116],"imposing":[97],"NLMC":[98],"latent":[101],"scene":[102],"signal.":[103],"Last,":[104],"provides":[106],"characterization":[109],"accounting":[111],"using":[117],"band-dependent":[119],"band-weighted":[124],"Mahalanobis":[125],"distance":[126],"similarity":[128],"measurement.":[129],"A":[130],"novel":[131],"optimization":[132],"method":[133],"based":[134],"expectation-maximization":[137],"(EM)":[138],"algorithm":[139],"purified":[142],"approach":[144],"is":[145],"used":[146],"to":[147],"solve":[149],"resulting":[151],"maximum":[152],"posterior":[154],"(MAP)":[155],"problem.":[156],"The":[157],"experiments":[158],"both":[160],"simulated":[161],"real":[163],"data":[165],"sets":[166],"demonstrate":[167],"that":[168],"visual":[170],"quality":[171],"accuracy":[174],"are":[175],"significantly":[176],"improved":[177],"proposed":[180],"compared":[182],"previous":[184],"methods.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
