{"id":"https://openalex.org/W2249336288","doi":"https://doi.org/10.1109/tgrs.2015.2465899","title":"Matrix-Based Discriminant Subspace Ensemble for Hyperspectral Image Spatial\u2013Spectral Feature Fusion","display_name":"Matrix-Based Discriminant Subspace Ensemble for Hyperspectral Image Spatial\u2013Spectral Feature Fusion","publication_year":2015,"publication_date":"2015-09-16","ids":{"openalex":"https://openalex.org/W2249336288","doi":"https://doi.org/10.1109/tgrs.2015.2465899","mag":"2249336288"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2015.2465899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2015.2465899","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/A5086507196","display_name":"Renlong Hang","orcid":"https://orcid.org/0000-0001-6046-3689"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Renlong Hang","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404959","display_name":"Qingshan Liu","orcid":"https://orcid.org/0000-0002-5512-6984"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingshan Liu","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100775391","display_name":"Huihui Song","orcid":"https://orcid.org/0000-0002-0751-2354"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huihui Song","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047679253","display_name":"Yubao Sun","orcid":"https://orcid.org/0000-0002-0462-3729"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubao Sun","raw_affiliation_strings":["Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing University of Information Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5086507196"],"corresponding_institution_ids":["https://openalex.org/I200845125"],"apc_list":null,"apc_paid":null,"fwci":14.21881836,"has_fulltext":false,"cited_by_count":92,"citation_normalized_percentile":{"value":0.99030528,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"54","issue":"2","first_page":"783","last_page":"794"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9957000017166138,"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":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8457454442977905},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8116503953933716},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7534030675888062},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7294973731040955},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6805527806282043},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5849165916442871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5792163014411926},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5297155380249023},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5218297839164734},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4810757637023926},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4660440981388092},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4513406753540039},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.42651355266571045},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.4120227098464966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3390201926231384},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2951483726501465},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07941648364067078}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8457454442977905},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8116503953933716},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7534030675888062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7294973731040955},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6805527806282043},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5849165916442871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5792163014411926},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5297155380249023},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5218297839164734},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4810757637023926},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4660440981388092},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4513406753540039},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.42651355266571045},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.4120227098464966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3390201926231384},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2951483726501465},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07941648364067078},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2015.2465899","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2015.2465899","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7900000214576721}],"awards":[{"id":"https://openalex.org/G2558533570","display_name":null,"funder_award_id":"61272223","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5436219376","display_name":null,"funder_award_id":"41501377","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6555796547","display_name":null,"funder_award_id":"61300162","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7208724564","display_name":null,"funder_award_id":"61532009","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/F4320322874","display_name":"Universit\u00e0 degli Studi di Pavia","ror":"https://ror.org/00s6t1f81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1971891445","https://openalex.org/W1974981350","https://openalex.org/W1979730959","https://openalex.org/W1993109245","https://openalex.org/W1998030734","https://openalex.org/W2001298023","https://openalex.org/W2002849025","https://openalex.org/W2005106632","https://openalex.org/W2019338222","https://openalex.org/W2022156723","https://openalex.org/W2043665634","https://openalex.org/W2059089906","https://openalex.org/W2059110141","https://openalex.org/W2063907334","https://openalex.org/W2064886835","https://openalex.org/W2072187267","https://openalex.org/W2077732237","https://openalex.org/W2090425484","https://openalex.org/W2097366995","https://openalex.org/W2097900616","https://openalex.org/W2098057602","https://openalex.org/W2099454382","https://openalex.org/W2107966405","https://openalex.org/W2114819256","https://openalex.org/W2118796925","https://openalex.org/W2122177361","https://openalex.org/W2127199143","https://openalex.org/W2137570937","https://openalex.org/W2148791530","https://openalex.org/W2150757437","https://openalex.org/W2150796457","https://openalex.org/W2153248467","https://openalex.org/W2153635508","https://openalex.org/W2159070926","https://openalex.org/W2162698522","https://openalex.org/W2163584563","https://openalex.org/W2164330327","https://openalex.org/W2164437025","https://openalex.org/W2167917621","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W3104925044","https://openalex.org/W4212883601","https://openalex.org/W4214680458","https://openalex.org/W4320339642","https://openalex.org/W6674755931"],"related_works":["https://openalex.org/W2782869875","https://openalex.org/W2380748039","https://openalex.org/W2759832987","https://openalex.org/W2115292902","https://openalex.org/W1983733476","https://openalex.org/W2311479510","https://openalex.org/W2017194723","https://openalex.org/W2944008297","https://openalex.org/W2949090459","https://openalex.org/W2118344708"],"abstract_inverted_index":{"Spatial-spectral":[0],"feature":[1,57,95],"fusion":[2],"is":[3,59,89,111],"well":[4,80],"acknowledged":[5],"as":[6,33],"an":[7],"effective":[8],"method":[9],"for":[10,41,61,97,118],"hyperspectral":[11],"(HS)":[12],"image":[13,51,121],"classification.":[14,42,98,122],"Many":[15],"previous":[16],"studies":[17],"have":[18],"been":[19],"devoted":[20],"to":[21,64,91,113],"this":[22,44],"subject.":[23],"However,":[24],"these":[25],"methods":[26],"often":[27],"regard":[28],"the":[29,66,71,76,82,93,102,141,144],"spatial-spectral":[30,56,83],"high-dimensional":[31],"data":[32,131],"1-D":[34],"vector":[35],"and":[36,70,137],"then":[37],"extract":[38],"informative":[39],"features":[40],"In":[43],"paper,":[45],"we":[46],"propose":[47],"a":[48,107,115],"new":[49],"HS":[50,120,128],"classification":[52],"method.":[53,146],"Specifically,":[54],"matrix-based":[55,86],"representation":[58],"designed":[60],"each":[62],"pixel":[63],"capture":[65],"local":[67],"spatial":[68],"contextual":[69],"spectral":[72],"information":[73],"of":[74,104,143],"all":[75],"bands,":[77],"which":[78],"can":[79],"preserve":[81],"correlation.":[84],"Then,":[85],"discriminant":[87],"analysis":[88],"adopted":[90],"learn":[92],"discriminative":[94,105],"subspace":[96,116],"To":[99],"further":[100],"improve":[101],"performance":[103],"subspace,":[106],"random":[108],"sampling":[109],"technique":[110],"used":[112],"produce":[114],"ensemble":[117],"final":[119],"Experiments":[123],"are":[124],"conducted":[125],"on":[126],"three":[127],"remote":[129],"sensing":[130],"sets":[132],"acquired":[133],"by":[134],"different":[135],"sensors,":[136],"experimental":[138],"results":[139],"demonstrate":[140],"efficiency":[142],"proposed":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":18},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}