{"id":"https://openalex.org/W2795844359","doi":"https://doi.org/10.1109/tgrs.2018.2814781","title":"Multiple Feature Kernel Sparse Representation Classifier for Hyperspectral Imagery","display_name":"Multiple Feature Kernel Sparse Representation Classifier for Hyperspectral Imagery","publication_year":2018,"publication_date":"2018-04-04","ids":{"openalex":"https://openalex.org/W2795844359","doi":"https://doi.org/10.1109/tgrs.2018.2814781","mag":"2795844359"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2814781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2814781","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/A5046938347","display_name":"Le Gan","orcid":"https://orcid.org/0000-0002-8260-6932"},"institutions":[{"id":"https://openalex.org/I4210141849","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210141849"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Le Gan","raw_affiliation_strings":["Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","Nanjing University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"]},{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000395252","display_name":"Junshi Xia","orcid":"https://orcid.org/0000-0002-5586-6536"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I4210124956","display_name":"Grenoble Images Parole Signal Automatique","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]}],"countries":["FR","JP"],"is_corresponding":false,"raw_author_name":"Junshi Xia","raw_affiliation_strings":["Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan","GIPSA - Signal Images Physique"],"affiliations":[{"raw_affiliation_string":"Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"GIPSA - Signal Images Physique","institution_ids":["https://openalex.org/I4210124956"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100690406","display_name":"Peijun Du","orcid":"https://orcid.org/0000-0002-2488-2656"},"institutions":[{"id":"https://openalex.org/I4210141849","display_name":"National Administration of Surveying, Mapping and Geoinformation of China","ror":"https://ror.org/04z3map19","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210141849"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peijun Du","raw_affiliation_strings":["Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","Nanjing University"],"affiliations":[{"raw_affiliation_string":"Key Laboratory for Satellite Mapping Technology and Applications of National Administration of Surveying, Mapping and Geoinformation of China, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"]},{"raw_affiliation_string":"Nanjing University","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210124956","display_name":"Grenoble Images Parole Signal Automatique","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"funder","lineage":["https://openalex.org/I1294671590"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["CNRS, Grenoble INP*, GIPSA-lab, Univ. Grenoble Alpes, Grenoble, France","GIPSA - Signal Images Physique"],"affiliations":[{"raw_affiliation_string":"CNRS, Grenoble INP*, GIPSA-lab, Univ. Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I1294671590"]},{"raw_affiliation_string":"GIPSA - Signal Images Physique","institution_ids":["https://openalex.org/I4210124956"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5046938347"],"corresponding_institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":4.937,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.9545296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"56","issue":"9","first_page":"5343","last_page":"5356"},"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":0.9939000010490417,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9578999876976013,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.8001792430877686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7450634241104126},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7151087522506714},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6024044752120972},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5985023975372314},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5691271424293518},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5684490203857422},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.487368643283844},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4864654242992401},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.48339834809303284},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.46397313475608826},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.4519602060317993},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32821959257125854}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.8001792430877686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7450634241104126},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7151087522506714},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6024044752120972},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5985023975372314},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5691271424293518},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5684490203857422},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.487368643283844},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4864654242992401},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.48339834809303284},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.46397313475608826},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.4519602060317993},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32821959257125854},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2018.2814781","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2814781","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"},{"id":"pmh:oai:HAL:hal-01960878v1","is_oa":false,"landing_page_url":"https://hal.science/hal-01960878","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing, 2018, 56 (9), pp.5343-5356. &#x27E8;10.1109/TGRS.2018.2814781&#x27E9;","raw_type":"Journal articles"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1069859310","display_name":null,"funder_award_id":"41471275","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6166494848","display_name":null,"funder_award_id":"41631176","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W1529476013","https://openalex.org/W1808256548","https://openalex.org/W1964749215","https://openalex.org/W1973521730","https://openalex.org/W1974981350","https://openalex.org/W1985133440","https://openalex.org/W1985636418","https://openalex.org/W1991888246","https://openalex.org/W1996236363","https://openalex.org/W1997565609","https://openalex.org/W2004754531","https://openalex.org/W2005876975","https://openalex.org/W2006500012","https://openalex.org/W2009286595","https://openalex.org/W2013251902","https://openalex.org/W2014158063","https://openalex.org/W2019338222","https://openalex.org/W2041100636","https://openalex.org/W2043665634","https://openalex.org/W2049444988","https://openalex.org/W2052160904","https://openalex.org/W2053852479","https://openalex.org/W2054502547","https://openalex.org/W2056302425","https://openalex.org/W2061572659","https://openalex.org/W2073786624","https://openalex.org/W2075707011","https://openalex.org/W2085400714","https://openalex.org/W2097915756","https://openalex.org/W2100975942","https://openalex.org/W2101711129","https://openalex.org/W2103094532","https://openalex.org/W2105386417","https://openalex.org/W2108597246","https://openalex.org/W2112447569","https://openalex.org/W2113199901","https://openalex.org/W2115451191","https://openalex.org/W2115718371","https://openalex.org/W2122662167","https://openalex.org/W2124372976","https://openalex.org/W2127152713","https://openalex.org/W2129812935","https://openalex.org/W2131697388","https://openalex.org/W2136251662","https://openalex.org/W2140095548","https://openalex.org/W2142848040","https://openalex.org/W2143354507","https://openalex.org/W2144348684","https://openalex.org/W2152057649","https://openalex.org/W2153635508","https://openalex.org/W2158400785","https://openalex.org/W2163352848","https://openalex.org/W2164330327","https://openalex.org/W2168809519","https://openalex.org/W2335607901","https://openalex.org/W2518815253","https://openalex.org/W2570194385","https://openalex.org/W2595650414","https://openalex.org/W2595902385","https://openalex.org/W2756138550","https://openalex.org/W2763375796","https://openalex.org/W3002694247","https://openalex.org/W4313169793","https://openalex.org/W4320339642","https://openalex.org/W6634974784","https://openalex.org/W6638482740","https://openalex.org/W6676727762"],"related_works":["https://openalex.org/W3000465807","https://openalex.org/W4394663664","https://openalex.org/W2014683590","https://openalex.org/W2351582470","https://openalex.org/W1980227981","https://openalex.org/W1984421104","https://openalex.org/W2512565647","https://openalex.org/W2001772920","https://openalex.org/W2393746448","https://openalex.org/W2905418897"],"abstract_inverted_index":{"Multiple":[0],"types":[1],"of":[2,26,82,96,148],"features,":[3,10,132],"e.g.,":[4],"spectral,":[5],"filtering,":[6],"texture,":[7],"and":[8,31,72,114,138,144,168],"shape":[9],"are":[11,94,142],"helpful":[12],"for":[13,126],"hyperspectral":[14,127],"image":[15],"(HSI)":[16],"classification":[17,36],"tasks.":[18],"Combining":[19],"multiple":[20,118],"features":[21],"can":[22,78,162],"describe":[23],"the":[24,47,58,66,80,89,179,190,195],"characteristics":[25],"pixels":[27],"from":[28],"different":[29,186],"perspectives,":[30],"always":[32],"results":[33,184],"in":[34,91,174],"better":[35],"performance.":[37],"Recently,":[38],"multifeature":[39,54],"combination":[40],"learning":[41],"has":[42],"been":[43],"widely":[44],"employed":[45],"to":[46,51],"multitask-learning-based":[48],"representation-based":[49,61,75,122],"model":[50],"obtain":[52],"a":[53,116,154,170],"representation":[55],"vector.":[56],"However,":[57],"linear":[59,83],"sparse":[60,74,121],"classifier":[62,76,123],"(SRC)":[63],"cannot":[64],"handle":[65,163],"HSI":[67],"with":[68,165],"highly":[69],"nonlinear":[70,87,166],"distribution,":[71],"kernel":[73,92,107,120,157,175],"(KSRC)":[77],"remedy":[79],"drawback":[81],"SRC.":[84],"By":[85],"adopting":[86],"mapping,":[88],"samples":[90],"space":[93,176],"often":[95],"high":[97],"or":[98],"even":[99],"infinite":[100],"dimensionality.":[101],"In":[102],"this":[103],"paper,":[104],"we":[105],"integrate":[106],"principal":[108],"component":[109],"analysis":[110],"into":[111,153],"multifeature-based":[112],"KSRC":[113],"propose":[115],"novel":[117],"feature":[119,149],"(namely,":[124],"MFKSRC)":[125],"imagery.":[128],"More":[129],"specifically,":[130],"spatial":[131],"Gabor":[133],"textures,":[134],"local":[135],"binary":[136],"patterns,":[137],"difference":[139],"morphological":[140],"profiles":[141],"adopted":[143],"then":[145],"each":[146],"kind":[147],"is":[150],"transformed":[151],"nonlinearly":[152],"new":[155],"low-dimensional":[156],"space.":[158],"The":[159],"proposed":[160,191],"framework":[161],"data":[164],"distribution":[167],"add":[169],"dimensionality":[171],"reduction":[172],"stage":[173],"before":[177],"optimizing":[178],"corresponding":[180],"cost":[181],"function.":[182],"Experimental":[183],"on":[185],"HSIs":[187],"demonstrate":[188],"that":[189],"MFKSRC":[192],"algorithm":[193],"outperforms":[194],"state-of-the-art":[196],"classifiers.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
