{"id":"https://openalex.org/W2901199499","doi":"https://doi.org/10.1109/igarss.2018.8517616","title":"Towards Weakly Pareto Optimal: An Improved Multi-Objective Based Band Selection Method for Hyperspectral Imagery","display_name":"Towards Weakly Pareto Optimal: An Improved Multi-Objective Based Band Selection Method for Hyperspectral Imagery","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901199499","doi":"https://doi.org/10.1109/igarss.2018.8517616","mag":"2901199499"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-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/A5049136910","display_name":"Bin Pan","orcid":"https://orcid.org/0000-0003-3063-1762"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Pan","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100328729","display_name":"Liming Wang","orcid":"https://orcid.org/0000-0002-5732-5258"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liming Wang","raw_affiliation_strings":["State Key Laboratory of Information Security, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Security, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018133348","display_name":"Xia Xu","orcid":"https://orcid.org/0000-0001-9743-3096"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Xu","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112124899","display_name":"Zhenwei Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenwei Shi","raw_affiliation_strings":["Image Processing Center, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Center, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6435,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.73227283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4705","last_page":"4708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9891999959945679,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.7724287509918213},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.6020985841751099},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6009197235107422},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.5979417562484741},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5574712753295898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5050047039985657},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.44663307070732117},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4361902177333832},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.435185968875885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4287011921405792},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3771873116493225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3731231093406677},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07773852348327637}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7724287509918213},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.6020985841751099},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6009197235107422},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.5979417562484741},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5574712753295898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5050047039985657},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.44663307070732117},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4361902177333832},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.435185968875885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4287011921405792},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3771873116493225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3731231093406677},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07773852348327637},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517616","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1902936532","https://openalex.org/W2008499862","https://openalex.org/W2071185414","https://openalex.org/W2143381319","https://openalex.org/W2316226477","https://openalex.org/W2566476692","https://openalex.org/W2747189523","https://openalex.org/W2761339476","https://openalex.org/W2770315464","https://openalex.org/W4292864963","https://openalex.org/W6746528787"],"related_works":["https://openalex.org/W2090178682","https://openalex.org/W2001591765","https://openalex.org/W4241467429","https://openalex.org/W2073147994","https://openalex.org/W1588199609","https://openalex.org/W2384474142","https://openalex.org/W1550055091","https://openalex.org/W2744462909","https://openalex.org/W3083133203","https://openalex.org/W1971520370"],"abstract_inverted_index":{"Band":[0],"selection":[1,46,64,92],"refers":[2],"to":[3,24,51,109],"finding":[4],"the":[5,25,29,40,43,69,84,88,104,111,114,121],"most":[6],"representative":[7],"channels":[8],"from":[9],"hyperspectral":[10,44],"images.":[11],"Usually,":[12],"certain":[13],"objective":[14],"functions":[15],"are":[16],"designed":[17],"and":[18,28,120,124],"combined":[19],"via":[20,94],"regularization":[21],"terms.":[22],"Owing":[23],"parameters":[26],"independence":[27],"optimal":[30],"solutions,":[31],"multi-objective":[32,62,89],"based":[33,61,90],"methods":[34,65],"have":[35],"presented":[36],"promising":[37],"performance.":[38],"However,":[39],"characteristics":[41],"of":[42,87,113,135],"band":[45,63,91],"problem":[47],"make":[48],"its":[49],"range":[50],"be":[52],"discrete.":[53],"In":[54,79],"this":[55,80,125],"case,":[56],"recently":[57],"proposed":[58,105],"weighted":[59,101],"Tchebycheff":[60,102],"could":[66],"only":[67],"reach":[68],"weakly":[70],"Pareto":[71,118],"optimal,":[72],"which":[73],"would":[74],"result":[75],"in":[76],"non-unique":[77],"solutions.":[78],"paper,":[81],"we":[82],"improve":[83],"decomposition":[85],"process":[86],"method":[93,106],"a":[95],"boundary":[96],"intersection":[97],"approach.":[98],"Compared":[99],"with":[100],"decomposition,":[103],"is":[107,127,138],"able":[108],"change":[110],"shape":[112],"contour":[115],"lines":[116],"between":[117],"Front":[119],"ideal":[122],"point,":[123],"approach":[126],"particularly":[128],"suitable":[129],"for":[130],"discrete-range":[131],"problems.":[132],"The":[133],"effectiveness":[134],"our":[136],"improvement":[137],"demonstrated":[139],"by":[140],"comparison":[141],"experiments.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
