{"id":"https://openalex.org/W2058484777","doi":"https://doi.org/10.1109/jstsp.2015.2419184","title":"Subspace Vertex Pursuit: A Fast and Robust Near-Separable Nonnegative Matrix Factorization Method for Hyperspectral Unmixing","display_name":"Subspace Vertex Pursuit: A Fast and Robust Near-Separable Nonnegative Matrix Factorization Method for Hyperspectral Unmixing","publication_year":2015,"publication_date":"2015-04-03","ids":{"openalex":"https://openalex.org/W2058484777","doi":"https://doi.org/10.1109/jstsp.2015.2419184","mag":"2058484777"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2015.2419184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2015.2419184","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","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/A5019924950","display_name":"Qing Qu","orcid":"https://orcid.org/0000-0001-9136-558X"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qing Qu","raw_affiliation_strings":["Electrical Engineering Department, Columbia University, New York, NY, USA","[Electrical Engineering Department, Columbia University, New York, NY, USA]"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"[Electrical Engineering Department, Columbia University, New York, NY, USA]","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021852735","display_name":"Nasser M. Nasrabadi","orcid":"https://orcid.org/0000-0001-8730-627X"},"institutions":[{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nasser M. Nasrabadi","raw_affiliation_strings":["Department of the Army, U.S. Army Research Laboratory, Adelphi, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of the Army, U.S. Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101413113","display_name":"Trac D. Tran","orcid":"https://orcid.org/0000-0002-0421-8416"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trac D. Tran","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","Dept. of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019924950"],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":4.5611,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.95113522,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"9","issue":"6","first_page":"1142","last_page":"1155"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9980000257492065,"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":0.9966999888420105,"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":0.8803584575653076},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6580377817153931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6129035353660583},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.6021141409873962},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5350301265716553},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5242472290992737},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5216715335845947},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4722917675971985},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4691064953804016},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46361643075942993},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4454426169395447},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4448881149291992},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4289506673812866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.390383243560791},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3348952829837799},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32702094316482544},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.0927504301071167}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8803584575653076},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6580377817153931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6129035353660583},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.6021141409873962},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5350301265716553},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5242472290992737},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5216715335845947},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4722917675971985},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4691064953804016},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46361643075942993},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4454426169395447},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4448881149291992},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4289506673812866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.390383243560791},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3348952829837799},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32702094316482544},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0927504301071167},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstsp.2015.2419184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2015.2419184","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1012505809","display_name":null,"funder_award_id":"CCF-1117545","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1222437328","display_name":null,"funder_award_id":"60219-MA","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G2049044860","display_name":null,"funder_award_id":"N000141210765","funder_id":"https://openalex.org/F4320337345","funder_display_name":"Office of Naval Research"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337345","display_name":"Office of Naval Research","ror":"https://ror.org/00rk2pe57"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1524090374","https://openalex.org/W1560324652","https://openalex.org/W1902027874","https://openalex.org/W1966872876","https://openalex.org/W1974774078","https://openalex.org/W1982755765","https://openalex.org/W1993335267","https://openalex.org/W2004594443","https://openalex.org/W2027878671","https://openalex.org/W2039806043","https://openalex.org/W2040325979","https://openalex.org/W2046793177","https://openalex.org/W2063790512","https://openalex.org/W2075665712","https://openalex.org/W2100549954","https://openalex.org/W2105503503","https://openalex.org/W2105693192","https://openalex.org/W2106642558","https://openalex.org/W2111604514","https://openalex.org/W2117986441","https://openalex.org/W2124172487","https://openalex.org/W2125118959","https://openalex.org/W2125298866","https://openalex.org/W2125860481","https://openalex.org/W2127062304","https://openalex.org/W2127495569","https://openalex.org/W2134328014","https://openalex.org/W2135029798","https://openalex.org/W2138038253","https://openalex.org/W2140318696","https://openalex.org/W2157321686","https://openalex.org/W2160979406","https://openalex.org/W2163547919","https://openalex.org/W2163886442","https://openalex.org/W2164278908","https://openalex.org/W2166864699","https://openalex.org/W2170395949","https://openalex.org/W2222512263","https://openalex.org/W2289917018","https://openalex.org/W2295820431","https://openalex.org/W2333836441","https://openalex.org/W2951002577","https://openalex.org/W2951085447","https://openalex.org/W2951734015","https://openalex.org/W3106127686","https://openalex.org/W3141222251","https://openalex.org/W3143596294","https://openalex.org/W4233760599","https://openalex.org/W4292363360","https://openalex.org/W6631434998","https://openalex.org/W6633456375","https://openalex.org/W6675164516","https://openalex.org/W6675606416","https://openalex.org/W6675881135","https://openalex.org/W6678827302","https://openalex.org/W6680012447","https://openalex.org/W6680770193","https://openalex.org/W6764566129"],"related_works":["https://openalex.org/W4308269461","https://openalex.org/W4281395053","https://openalex.org/W2020769413","https://openalex.org/W2127243424","https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640"],"abstract_inverted_index":{"The":[0],"separability":[1],"assumption":[2,17],"turns":[3],"the":[4,14,23,34,40,51,74,78,83,128,131],"nonnegative":[5],"matrix":[6],"factorization":[7],"(NMF)":[8],"problem":[9,42,48,65],"tractable,":[10],"which":[11],"coincides":[12],"with":[13,73],"pure":[15],"pixel":[16],"and":[18,31,112,123],"provides":[19],"new":[20],"insights":[21],"for":[22,63],"hyperspectral":[24,125],"unmixing":[25,41],"problem.":[26],"Based":[27],"on":[28,120],"this":[29,64],"assumption,":[30],"starting":[32],"from":[33],"data":[35,52],"self-expressiveness":[36],"perspective,":[37],"we":[38,58],"formulate":[39],"as":[43,54],"a":[44,55,60,68,88],"joint":[45],"sparse":[46],"recovery":[47],"by":[49,66,86],"using":[50],"itself":[53],"dictionary.":[56],"Moreover,":[57],"present":[59],"quasi-greedy":[61],"algorithm":[62],"employing":[67],"back-tracking":[69],"strategy.":[70],"In":[71],"comparison":[72],"previous":[75],"greedy":[76],"methods,":[77],"proposed":[79,132],"method":[80,98],"can":[81],"refresh":[82],"candidate":[84],"pixels":[85],"solving":[87],"small":[89],"fixed-scale":[90],"convex":[91],"sub-problem":[92],"in":[93],"every":[94],"iteration.":[95],"Therefore,":[96],"our":[97],"has":[99],"two":[100],"important":[101],"characteristics:":[102],"(i)":[103],"enhanced":[104],"robustness":[105],"against":[106],"noise;":[107],"(ii)":[108],"moderate":[109],"computational":[110],"complexity":[111],"scalability":[113],"to":[114],"large":[115],"dataset.":[116],"Finally,":[117],"computer":[118],"simulations":[119],"both":[121],"synthetic":[122],"real":[124],"datasets":[126],"demonstrate":[127],"effectiveness":[129],"of":[130],"method.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
