{"id":"https://openalex.org/W2897121118","doi":"https://doi.org/10.1109/lgrs.2018.2872540","title":"Band Selection of Hyperspectral Images Using Multiobjective Optimization-Based Sparse Self-Representation","display_name":"Band Selection of Hyperspectral Images Using Multiobjective Optimization-Based Sparse Self-Representation","publication_year":2018,"publication_date":"2018-10-16","ids":{"openalex":"https://openalex.org/W2897121118","doi":"https://doi.org/10.1109/lgrs.2018.2872540","mag":"2897121118"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2018.2872540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2018.2872540","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5101961438","display_name":"Peng Hu","orcid":"https://orcid.org/0000-0001-9642-1608"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Hu","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062400971","display_name":"Xiaobo Liu","orcid":"https://orcid.org/0000-0001-8298-7715"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobo Liu","raw_affiliation_strings":["Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044359278","display_name":"Yaoming Cai","orcid":"https://orcid.org/0000-0002-2609-3036"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaoming Cai","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038861185","display_name":"Zhihua Cai","orcid":"https://orcid.org/0000-0003-0020-6503"},"institutions":[{"id":"https://openalex.org/I4210105374","display_name":"Beibu Gulf University","ror":"https://ror.org/01dq3qq95","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210105374"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihua Cai","raw_affiliation_strings":["Beibu Gulf Big Data Resources Utilization Lab, Qinzhou University, Qinzhou, China"],"affiliations":[{"raw_affiliation_string":"Beibu Gulf Big Data Resources Utilization Lab, Qinzhou University, Qinzhou, China","institution_ids":["https://openalex.org/I4210105374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101961438"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":4.1678,"has_fulltext":false,"cited_by_count":63,"citation_normalized_percentile":{"value":0.94596604,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"16","issue":"3","first_page":"452","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9915000200271606,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.7647119760513306},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.630512535572052},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6048063039779663},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5969162583351135},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.5601156949996948},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5234034657478333},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5137070417404175},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5020430088043213},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.46483537554740906},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4379889965057373},{"id":"https://openalex.org/keywords/coefficient-matrix","display_name":"Coefficient matrix","score":0.43546515703201294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31772780418395996},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19087687134742737},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.1783660352230072}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7647119760513306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.630512535572052},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6048063039779663},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5969162583351135},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.5601156949996948},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5234034657478333},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5137070417404175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5020430088043213},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.46483537554740906},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4379889965057373},{"id":"https://openalex.org/C60866291","wikidata":"https://www.wikidata.org/wiki/Q5140577","display_name":"Coefficient matrix","level":3,"score":0.43546515703201294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31772780418395996},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19087687134742737},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.1783660352230072},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2018.2872540","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2018.2872540","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G301648404","display_name":null,"funder_award_id":"61773355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3037517755","display_name":null,"funder_award_id":"CUGL17022","funder_id":"https://openalex.org/F4320322815","funder_display_name":"China University of Geosciences, Wuhan"},{"id":"https://openalex.org/G4220299630","display_name":null,"funder_award_id":"61603355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5580311328","display_name":null,"funder_award_id":"2018CFB528","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"},{"id":"https://openalex.org/G6847820486","display_name":null,"funder_award_id":"6177021501","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/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null},{"id":"https://openalex.org/F4320322815","display_name":"China University of Geosciences, Wuhan","ror":"https://ror.org/04q6c7p66"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1529476013","https://openalex.org/W1902936532","https://openalex.org/W1932531222","https://openalex.org/W1978567114","https://openalex.org/W2012255037","https://openalex.org/W2088657558","https://openalex.org/W2109836508","https://openalex.org/W2126105956","https://openalex.org/W2130187411","https://openalex.org/W2167159964","https://openalex.org/W2170792849","https://openalex.org/W2340318445","https://openalex.org/W2548041193","https://openalex.org/W2744049245","https://openalex.org/W2747189523","https://openalex.org/W2761339476","https://openalex.org/W2765968907","https://openalex.org/W2782517596","https://openalex.org/W2793272303","https://openalex.org/W2793946261","https://openalex.org/W6631952016"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2374021060"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1],"(HSIs)":[2],"consist":[3],"of":[4,6,99,112,141],"hundreds":[5],"continuous":[7],"bands":[8,27,167],"with":[9,88,145,168],"high":[10],"correlation,":[11],"making":[12,55],"it":[13,56],"contain":[14],"great":[15],"abundant":[16],"information.":[17],"Band":[18],"selection":[19,41],"is":[20,131,161],"an":[21,44],"effective":[22],"idea":[23],"for":[24,123,150],"removing":[25],"redundant":[26],"and":[28,51,108],"preserving":[29],"the":[30,34,61,100,105,134,139,142,158],"physical":[31],"significance":[32],"at":[33],"same":[35],"time.":[36],"Popular":[37],"sparse":[38,52,84,101],"representation-based":[39],"band":[40,129],"commonly":[42],"introduces":[43],"additional":[45],"coefficient":[46,107],"to":[47,58,81,118,163],"combine":[48],"error":[49],"term":[50],"constraint":[53],"term,":[54],"difficult":[57],"find":[59],"out":[60],"optimal":[62,113],"balance":[63,106],"coefficient.":[64],"In":[65],"this":[66],"letter,":[67],"we":[68],"propose":[69],"a":[70,83,110,120,127],"hybrid":[71],"clustering-based":[72],"band-selection":[73,148],"approach":[74,94,144,160],"based":[75],"on":[76],"using":[77],"evolutionary":[78],"multiobjective":[79],"optimization":[80],"solve":[82],"self-representation":[85],"model":[86],"constituted":[87],"two":[89,97],"conflicting":[90],"objectives.":[91],"The":[92],"proposed":[93,143,159],"simultaneously":[95],"minimizes":[96],"terms":[98],"representation":[102],"model,":[103],"avoiding":[104],"producing":[109],"set":[111],"solutions":[114],"that":[115,157],"are":[116],"used":[117],"construct":[119],"similarity":[121],"matrix":[122],"spectral":[124],"clustering.":[125],"Finally,":[126],"reduced":[128],"subset":[130],"determined":[132],"by":[133],"cluster":[135],"centers.":[136],"We":[137],"compare":[138],"results":[140],"four":[146],"existing":[147],"methods":[149],"three":[151],"real":[152],"HSI":[153],"data":[154],"sets,":[155],"showing":[156],"able":[162],"effectively":[164],"select":[165],"representative":[166],"better":[169],"classification":[170],"accuracy.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-15T09:29:46.208133","created_date":"2025-10-10T00:00:00"}