{"id":"https://openalex.org/W2028623420","doi":"https://doi.org/10.1109/tgrs.2013.2285049","title":"Spatial\u2013Spectral Classification of Hyperspectral Images Using Discriminative Dictionary Designed by Learning Vector Quantization","display_name":"Spatial\u2013Spectral Classification of Hyperspectral Images Using Discriminative Dictionary Designed by Learning Vector Quantization","publication_year":2013,"publication_date":"2013-11-19","ids":{"openalex":"https://openalex.org/W2028623420","doi":"https://doi.org/10.1109/tgrs.2013.2285049","mag":"2028623420"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2013.2285049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2013.2285049","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/A5068625652","display_name":"Zhaowen Wang","orcid":"https://orcid.org/0000-0002-4605-2506"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaowen Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana\u2013Champaign, Urbana, IL, USA","Dept of Electr. & Comput. Engg, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana\u2013Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Dept of Electr. & Comput. Engg, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"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":["U.S. Army Research Laboratory, Adelphi, MD, USA","U.S. Army Research Lab, Adelphi, MD, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"U.S. Army Research Laboratory, Adelphi, MD, USA","institution_ids":["https://openalex.org/I166416128"]},{"raw_affiliation_string":"U.S. Army Research Lab, Adelphi, MD, USA#TAB#","institution_ids":["https://openalex.org/I166416128"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101457342","display_name":"Thomas S. Huang","orcid":"https://orcid.org/0000-0001-8474-5859"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Thomas S. Huang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana\u2013Champaign, Urbana, IL, USA","Dept of Electr. & Comput. Engg, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana\u2013Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]},{"raw_affiliation_string":"Dept of Electr. & Comput. Engg, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":14.4521,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.99004494,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"52","issue":"8","first_page":"4808","last_page":"4822"},"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":0.9912999868392944,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9861999750137329,"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":0.9138234853744507},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8063746690750122},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6952319741249084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6706676483154297},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.6610855460166931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6479943990707397},{"id":"https://openalex.org/keywords/learning-vector-quantization","display_name":"Learning vector quantization","score":0.5441736578941345},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4944610595703125},{"id":"https://openalex.org/keywords/dictionary-learning","display_name":"Dictionary learning","score":0.47438672184944153},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4362139105796814},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4258421063423157},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.4203265309333801},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3614118695259094},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14474710822105408},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08924832940101624}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9138234853744507},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8063746690750122},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6952319741249084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6706676483154297},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.6610855460166931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6479943990707397},{"id":"https://openalex.org/C40567965","wikidata":"https://www.wikidata.org/wiki/Q1820283","display_name":"Learning vector quantization","level":3,"score":0.5441736578941345},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4944610595703125},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.47438672184944153},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4362139105796814},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4258421063423157},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.4203265309333801},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3614118695259094},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14474710822105408},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08924832940101624}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2013.2285049","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2013.2285049","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":[{"score":0.7900000214576721,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G934873480","display_name":null,"funder_award_id":"W911NF-09-1-0383","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W283029246","https://openalex.org/W628438000","https://openalex.org/W1507028917","https://openalex.org/W1606936601","https://openalex.org/W1967212196","https://openalex.org/W1972715665","https://openalex.org/W1990586396","https://openalex.org/W1990863955","https://openalex.org/W1998030734","https://openalex.org/W2005876975","https://openalex.org/W2027805700","https://openalex.org/W2084716923","https://openalex.org/W2097915756","https://openalex.org/W2104269704","https://openalex.org/W2111975408","https://openalex.org/W2113606819","https://openalex.org/W2114819256","https://openalex.org/W2115429828","https://openalex.org/W2127199143","https://openalex.org/W2128638419","https://openalex.org/W2129812935","https://openalex.org/W2130951397","https://openalex.org/W2131697388","https://openalex.org/W2131864940","https://openalex.org/W2132283655","https://openalex.org/W2135780853","https://openalex.org/W2136251662","https://openalex.org/W2139054653","https://openalex.org/W2145035344","https://openalex.org/W2146926923","https://openalex.org/W2149471024","https://openalex.org/W2149861038","https://openalex.org/W2160547390","https://openalex.org/W2162480849","https://openalex.org/W2163112044","https://openalex.org/W2164330327","https://openalex.org/W2164452299","https://openalex.org/W2164626806","https://openalex.org/W2169574652","https://openalex.org/W2478493250","https://openalex.org/W2552220127","https://openalex.org/W2953139536","https://openalex.org/W3102566946","https://openalex.org/W3144858519","https://openalex.org/W4237640996","https://openalex.org/W6642098062","https://openalex.org/W6676903177","https://openalex.org/W6678757208","https://openalex.org/W6685272531"],"related_works":["https://openalex.org/W2100968651","https://openalex.org/W4243803532","https://openalex.org/W2352648934","https://openalex.org/W4230688072","https://openalex.org/W1915693853","https://openalex.org/W2378212145","https://openalex.org/W2798892016","https://openalex.org/W2100492357","https://openalex.org/W2202992072","https://openalex.org/W2181453615"],"abstract_inverted_index":{"In":[0,22,117],"this":[1],"paper,":[2],"a":[3,24,76,123,133,145,150],"novel":[4],"discriminative":[5],"dictionary":[6,25,62,93,104,160,193,207],"learning":[7,70,98,208],"method":[8,184,203],"is":[9,26,36,81,130,138],"proposed":[10,202],"for":[11,57,92,122],"sparse-representation-based":[12],"classification":[13,86,188],"(SRC)":[14],"to":[15,41,84,112,161],"label":[16],"highly":[17],"dimensional":[18],"hyperspectral":[19],"imagery":[20],"(HSI).":[21],"SRC,":[23],"conventionally":[27],"constructed":[28],"using":[29,132,182,196],"all":[30],"of":[31,45,144,158],"the":[32,42,61,66,69,85,89,119,141,163,169,179,197,212,217],"training":[33,199],"pixels,":[34],"which":[35,154],"not":[37],"only":[38],"inefficient":[39],"due":[40],"large":[43],"size":[44,194],"typical":[46],"HSI":[47,175],"images":[48,176],"but":[49],"also":[50,204],"ineffective":[51],"in":[52,149,215],"capturing":[53],"class-discriminative":[54],"information":[55],"crucial":[56],"classification.":[58],"We":[59],"address":[60],"design":[63],"problem":[64],"with":[65,140,190],"inspiration":[67],"from":[68],"vector":[71],"quantization":[72],"technique":[73],"and":[74,102,137,210,219],"propose":[75],"hinge":[77],"loss":[78],"function":[79,91],"that":[80,107,167,178],"directly":[82],"related":[83],"task":[87],"as":[88],"objective":[90],"learning.":[94],"The":[95,201],"resulting":[96],"online":[97],"procedure":[99],"systematically":[100],"\u201cpulls\u201d":[101],"\u201cpushes\u201d":[103],"atoms":[105],"so":[106],"they":[108],"become":[109],"better":[110],"adapted":[111],"distinguish":[113],"between":[114],"different":[115,174],"classes.":[116],"addition,":[118],"spatial":[120,164],"context":[121],"test":[124,147],"pixel":[125,148],"within":[126],"its":[127],"local":[128],"neighborhood":[129],"modeled":[131],"Bayesian":[134],"graph":[135],"model":[136],"incorporated":[139],"sparse":[142],"representation":[143],"single":[146],"unified":[151],"probabilistic":[152],"framework,":[153],"enables":[155],"further":[156],"refinement":[157],"our":[159,183],"capture":[162],"class":[165],"dependence":[166],"complements":[168],"spectral":[170],"information.":[171],"Experiments":[172],"on":[173],"demonstrate":[177],"dictionaries":[180],"optimized":[181],"can":[185],"achieve":[186],"higher":[187],"accuracy":[189],"substantially":[191],"reduced":[192],"than":[195],"whole":[198],"set.":[200],"outperforms":[205],"existing":[206],"methods":[209],"attains":[211],"state-of-the-art":[213],"results":[214],"both":[216],"spectral-only":[218],"spatial-spectral":[220],"settings.":[221]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}