{"id":"https://openalex.org/W2547121314","doi":"https://doi.org/10.1109/whispers.2012.6874325","title":"Globally maximizing, locally minimizing: Regularized Nonnegative Matrix Factorization for hyperspectral data feature extraction","display_name":"Globally maximizing, locally minimizing: Regularized Nonnegative Matrix Factorization for hyperspectral data feature extraction","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2547121314","doi":"https://doi.org/10.1109/whispers.2012.6874325","mag":"2547121314"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2012.6874325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2012.6874325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5086729425","display_name":"Mingyi He","orcid":"https://orcid.org/0000-0003-2051-6955"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingyi He","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Feng Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Wei","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024631382","display_name":"Xiuping Jia","orcid":"https://orcid.org/0000-0001-9916-6382"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiuping Jia","raw_affiliation_strings":["School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.38959614,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"4"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9951000213623047,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9944999814033508,"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/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.8180348873138428},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7358813285827637},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.599195659160614},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.5734558701515198},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5681724548339844},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.5518273115158081},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5229911804199219},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5124719738960266},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.484379380941391},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4720041751861572},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4652095437049866},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4391283392906189},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42671138048171997},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.42525768280029297},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4243861436843872},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4193321168422699},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.11437362432479858}],"concepts":[{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.8180348873138428},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7358813285827637},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.599195659160614},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.5734558701515198},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5681724548339844},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.5518273115158081},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5229911804199219},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5124719738960266},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.484379380941391},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4720041751861572},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4652095437049866},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4391283392906189},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42671138048171997},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.42525768280029297},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4243861436843872},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4193321168422699},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.11437362432479858},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2012.6874325","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2012.6874325","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W178113997","https://openalex.org/W1902027874","https://openalex.org/W2097308346","https://openalex.org/W2104290444","https://openalex.org/W2117553576","https://openalex.org/W2131273085","https://openalex.org/W2131697388","https://openalex.org/W2142584058","https://openalex.org/W2143103810","https://openalex.org/W2341545927","https://openalex.org/W4250589301","https://openalex.org/W6607212033"],"related_works":["https://openalex.org/W4281395053","https://openalex.org/W4308269461","https://openalex.org/W2020769413","https://openalex.org/W2766940489","https://openalex.org/W2513087981","https://openalex.org/W2127243424","https://openalex.org/W2292979300","https://openalex.org/W2037504162","https://openalex.org/W2149305241","https://openalex.org/W4294224199"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,80,115],"find":[3,81],"a":[4,22,44,48,82,121,135],"compact":[5],"representation":[6],"which":[7,52],"uncovers":[8],"the":[9,15,61,70,76,87,92,117,127],"hidden":[10],"topics":[11],"and":[12,63,90,101],"simultaneously":[13,85],"respects":[14],"intrinsic":[16],"geometric":[17],"structure":[18],"of":[19,47],"hyperspectral":[20,123],"data,":[21],"novel":[23],"algorithm,":[24,37],"named":[25],"GLNMF":[26,68,98],"(Globally":[27],"maximizing,":[28],"Locally":[29],"minimizing,":[30],"regularized":[31],"Nonnegative":[32],"Matrix":[33],"Factorization)":[34],"feature":[35],"extraction":[36],"is":[38,43,113],"proposed.":[39],"The":[40],"proposed":[41,114,128],"algorithm":[42,112],"linear":[45],"approximation":[46],"multi-manifolds-based":[49],"learning":[50],"framework":[51],"imposes":[53],"an":[54],"additional":[55],"constraint":[56],"on":[57,120],"NMF":[58,131],"that":[59,84,126],"both":[60],"local":[62,71,93],"non-local":[64,77,88],"quantities":[65],"are":[66],"considered.":[67],"characterizes":[69],"scatter":[72,89],"as":[73,75,132,134],"well":[74,133],"scatter,":[78],"seeking":[79],"projection":[83],"maximizes":[86],"minimizes":[91],"scatter.":[94],"This":[95],"characteristic":[96],"makes":[97],"more":[99,102],"intuitive":[100],"powerful":[103],"than":[104],"some":[105],"up-to-date":[106],"methods.":[107,140],"An":[108],"iterative":[109],"multiplicative":[110],"updating":[111],"optimize":[116],"objective.":[118],"Experiments":[119],"benchmark":[122],"dataset":[124],"demonstrate":[125],"method":[129],"outperforms":[130],"few":[136],"current":[137],"dimensionality":[138],"reduction":[139]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}