{"id":"https://openalex.org/W2065548527","doi":"https://doi.org/10.1109/tgrs.2010.2068053","title":"An approach based on constrained nonnegative matrix factorization to unmix hyperspectral data","display_name":"An approach based on constrained nonnegative matrix factorization to unmix hyperspectral data","publication_year":2010,"publication_date":"2010-09-29","ids":{"openalex":"https://openalex.org/W2065548527","doi":"https://doi.org/10.1109/tgrs.2010.2068053","mag":"2065548527"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2010.2068053","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2010.2068053","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/A5100671625","display_name":"Xuesong Liu","orcid":"https://orcid.org/0000-0002-8285-3992"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Liu","raw_affiliation_strings":["Department of Electronic Engineering, Fudan University, Shanghai, China","Dept. of Electron. Eng., Fudan Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Fudan Univ., Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100705293","display_name":"Wei Xia","orcid":"https://orcid.org/0000-0003-3368-4050"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Xia","raw_affiliation_strings":["Department of Electronic Engineering, Fudan University, Shanghai, China","Dept. of Electron. Eng., Fudan Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Fudan Univ., Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059575276","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0003-4748-6426"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["Department of Electronic Engineering and the Key Laboratory of Wave Scattering and Remote Sensing Information, Fudan University, Shanghai, China","Dept. of Electron. Eng., Fudan Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and the Key Laboratory of Wave Scattering and Remote Sensing Information, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Fudan Univ., Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100461464","display_name":"Liming Zhang","orcid":"https://orcid.org/0000-0001-6795-3381"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liming Zhang","raw_affiliation_strings":["Department of Electronic Engineering, Fudan University, Shanghai, China","Dept. of Electron. Eng., Fudan Univ., Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Fudan Univ., Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":12.7199,"has_fulltext":false,"cited_by_count":171,"citation_normalized_percentile":{"value":0.98606163,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"49","issue":"2","first_page":"757","last_page":"772"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9026082158088684},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8984699249267578},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.6361694931983948},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6127200126647949},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5642926096916199},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.5172213315963745},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5042434930801392},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.495672345161438},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46376678347587585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45448634028434753},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4389359652996063},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.412566214799881},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3679566979408264},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34386828541755676}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9026082158088684},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8984699249267578},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.6361694931983948},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6127200126647949},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5642926096916199},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.5172213315963745},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5042434930801392},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.495672345161438},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46376678347587585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45448634028434753},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4389359652996063},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.412566214799881},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3679566979408264},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34386828541755676},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"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":1,"locations":[{"id":"doi:10.1109/tgrs.2010.2068053","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2010.2068053","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W65725463","https://openalex.org/W1508694032","https://openalex.org/W1532610010","https://openalex.org/W1548802052","https://openalex.org/W1902027874","https://openalex.org/W1914599625","https://openalex.org/W1965555277","https://openalex.org/W1968845542","https://openalex.org/W1976391658","https://openalex.org/W2002519017","https://openalex.org/W2002744657","https://openalex.org/W2003648194","https://openalex.org/W2005073772","https://openalex.org/W2015583498","https://openalex.org/W2017288758","https://openalex.org/W2019249717","https://openalex.org/W2070424424","https://openalex.org/W2090862158","https://openalex.org/W2098295833","https://openalex.org/W2099595379","https://openalex.org/W2101837437","https://openalex.org/W2102159812","https://openalex.org/W2107120407","https://openalex.org/W2107222994","https://openalex.org/W2110096996","https://openalex.org/W2113951177","https://openalex.org/W2114486983","https://openalex.org/W2116216716","https://openalex.org/W2118718620","https://openalex.org/W2118943995","https://openalex.org/W2123838014","https://openalex.org/W2127062304","https://openalex.org/W2128090514","https://openalex.org/W2131541495","https://openalex.org/W2135029798","https://openalex.org/W2140318696","https://openalex.org/W2140501674","https://openalex.org/W2141224535","https://openalex.org/W2145554279","https://openalex.org/W2147043781","https://openalex.org/W2156458885","https://openalex.org/W2157321686","https://openalex.org/W2165755981","https://openalex.org/W2169466597","https://openalex.org/W2295820431","https://openalex.org/W2312997001","https://openalex.org/W2406093411","https://openalex.org/W4205778870","https://openalex.org/W4233760599","https://openalex.org/W4248253651","https://openalex.org/W4297787516","https://openalex.org/W6630391810","https://openalex.org/W6675750237","https://openalex.org/W6677759377","https://openalex.org/W6679740048","https://openalex.org/W6680012447"],"related_works":["https://openalex.org/W2089298795","https://openalex.org/W1980988957","https://openalex.org/W2773002387","https://openalex.org/W2766484909","https://openalex.org/W2802800261","https://openalex.org/W1992367803","https://openalex.org/W2163867257","https://openalex.org/W2811256493","https://openalex.org/W2059578032","https://openalex.org/W2898368675"],"abstract_inverted_index":{"Nonnegative":[0],"matrix":[1],"factorization":[2],"(NMF)":[3],"has":[4,31],"been":[5],"recently":[6],"applied":[7],"to":[8,39,49,144,202],"solve":[9],"the":[10,23,29,40,44,59,86,111,116,147,154,168,175,181,194,197],"hyperspectral":[11,97,191],"unmixing":[12],"problem":[13],"because":[14],"it":[15],"ensures":[16],"nonnegativity":[17],"and":[18,72,83,115,133,172,189],"needs":[19],"no":[20],"assumption":[21],"for":[22],"presence":[24],"of":[25,35,43,96,110,149,170,177,196],"pure":[26],"pixels.":[27],"However,":[28],"algorithm":[30,143,165,199],"a":[32,66,107,141],"large":[33],"amount":[34],"local":[36,178],"minima":[37,179],"due":[38],"obvious":[41],"nonconvexity":[42],"objective":[45],"function.":[46],"In":[47,61],"order":[48],"improve":[50,146],"its":[51],"performance,":[52],"auxiliary":[53,155],"constraints":[54,90,156],"can":[55],"be":[56],"introduced":[57],"into":[58,85],"algorithm.":[60,88],"this":[62],"paper,":[63],"we":[64],"propose":[65,140],"new":[67],"approach":[68],"named":[69],"abundance":[70,81],"separation":[71,82],"smoothness":[73],"constrained":[74],"NMF":[75,87,171],"by":[76],"introducing":[77],"two":[78,94],"constraints,":[79],"namely,":[80],"smoothness,":[84],"These":[89],"are":[91,157],"based":[92,186],"on":[93,187],"properties":[95],"imagery.":[98],"First,":[99],"usually,":[100],"every":[101],"ground":[102,128],"object":[103],"presents":[104],"dominance":[105],"in":[106],"specific":[108],"region":[109],"entire":[112],"image":[113],"scene":[114],"correlation":[117],"is":[118],"weak":[119],"between":[120],"different":[121],"endmembers.":[122],"Second,":[123],"moving":[124],"through":[125],"various":[126],"regions,":[127],"objects":[129],"usually":[130],"vary":[131],"slowly":[132],"abrupt":[134],"changes":[135],"rarely":[136],"appear.":[137],"We":[138],"also":[139],"learning":[142],"further":[145],"performance":[148],"our":[150],"method,":[151],"from":[152],"which":[153],"removed":[158],"at":[159,180],"an":[160],"appropriate":[161],"time.":[162,183],"The":[163],"proposed":[164,198],"retains":[166],"all":[167],"advantages":[169],"effectively":[173],"overcomes":[174],"shortcoming":[176],"same":[182],"Experimental":[184],"results":[185],"synthetic":[188],"real":[190],"data":[192],"show":[193],"superiority":[195],"with":[200],"respect":[201],"other":[203],"state-of-the-art":[204],"approaches.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":14},{"year":2016,"cited_by_count":25},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":13},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":13}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}