{"id":"https://openalex.org/W1579487182","doi":"https://doi.org/10.1109/jstars.2015.2424433","title":"Semisupervised Pair-Wise Band Selection for Hyperspectral Images","display_name":"Semisupervised Pair-Wise Band Selection for Hyperspectral Images","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1579487182","doi":"https://doi.org/10.1109/jstars.2015.2424433","mag":"1579487182"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2015.2424433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2015.2424433","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"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/A5110376155","display_name":"Jun Bai","orcid":"https://orcid.org/0000-0002-1408-4271"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Bai","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040673285","display_name":"Shiming Xiang","orcid":"https://orcid.org/0000-0002-2089-9733"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiming Xiang","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110615722","display_name":"Limin Shi","orcid":null},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Limin Shi","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435212","display_name":"Chunhong Pan","orcid":"https://orcid.org/0000-0001-7433-4474"},"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"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunhong Pan","raw_affiliation_strings":["National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]},{"raw_affiliation_string":"National Laboratory of Pattern Recognition NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":null,"fwci":3.3671,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93011708,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"8","issue":"6","first_page":"2798","last_page":"2813"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9799000024795532,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9764999747276306,"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/bhattacharyya-distance","display_name":"Bhattacharyya distance","score":0.876865029335022},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.756353497505188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.722975492477417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6867964863777161},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5939777493476868},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5546059012413025},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5330204963684082},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47866591811180115},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.47553062438964844},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.4395281672477722},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.42589014768600464},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34126901626586914},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.20913636684417725},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1882742941379547},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.08926689624786377}],"concepts":[{"id":"https://openalex.org/C24145651","wikidata":"https://www.wikidata.org/wiki/Q2901249","display_name":"Bhattacharyya distance","level":2,"score":0.876865029335022},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.756353497505188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.722975492477417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6867964863777161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5939777493476868},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5546059012413025},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5330204963684082},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47866591811180115},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.47553062438964844},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.4395281672477722},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.42589014768600464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34126901626586914},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.20913636684417725},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1882742941379547},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.08926689624786377},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jstars.2015.2424433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstars.2015.2424433","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":false,"is_in_doaj":true,"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 Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G2531950031","display_name":null,"funder_award_id":"61305049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2557922004","display_name":null,"funder_award_id":"61403377","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5066778879","display_name":null,"funder_award_id":"91338202","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5307582445","display_name":"\u7ed3\u6784\u5316\u5224\u522b\u5b57\u5178\u5b66\u4e60\u65b9\u6cd5\u53ca\u5176\u5e94\u7528\u7814\u7a76","funder_award_id":"61272331","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W91932901","https://openalex.org/W1479807131","https://openalex.org/W1491300635","https://openalex.org/W1510526001","https://openalex.org/W1570876803","https://openalex.org/W1585385982","https://openalex.org/W1976359033","https://openalex.org/W2017360846","https://openalex.org/W2017856447","https://openalex.org/W2028436154","https://openalex.org/W2033515137","https://openalex.org/W2043051613","https://openalex.org/W2043665634","https://openalex.org/W2043945532","https://openalex.org/W2046373373","https://openalex.org/W2047029347","https://openalex.org/W2049365101","https://openalex.org/W2073786624","https://openalex.org/W2078491260","https://openalex.org/W2080322700","https://openalex.org/W2089372326","https://openalex.org/W2098057602","https://openalex.org/W2098622092","https://openalex.org/W2099189653","https://openalex.org/W2103568877","https://openalex.org/W2104290444","https://openalex.org/W2104990616","https://openalex.org/W2106092565","https://openalex.org/W2106777458","https://openalex.org/W2109483772","https://openalex.org/W2109836508","https://openalex.org/W2113464037","https://openalex.org/W2114819256","https://openalex.org/W2118286367","https://openalex.org/W2124834959","https://openalex.org/W2129652905","https://openalex.org/W2131697388","https://openalex.org/W2132060017","https://openalex.org/W2132549764","https://openalex.org/W2135496738","https://openalex.org/W2136504847","https://openalex.org/W2138038253","https://openalex.org/W2138583748","https://openalex.org/W2138963285","https://openalex.org/W2139206670","https://openalex.org/W2143277109","https://openalex.org/W2143984715","https://openalex.org/W2144086405","https://openalex.org/W2150990614","https://openalex.org/W2151288205","https://openalex.org/W2151599207","https://openalex.org/W2153409933","https://openalex.org/W2153635508","https://openalex.org/W2155359044","https://openalex.org/W2158001550","https://openalex.org/W2158994553","https://openalex.org/W2160410712","https://openalex.org/W2161943337","https://openalex.org/W2164330327","https://openalex.org/W2165379615","https://openalex.org/W2169042894","https://openalex.org/W2171350553","https://openalex.org/W2172142075","https://openalex.org/W2997701990","https://openalex.org/W3120421331","https://openalex.org/W4320339642","https://openalex.org/W6603746958","https://openalex.org/W6630424276","https://openalex.org/W6635184699","https://openalex.org/W6675747103","https://openalex.org/W6676565290","https://openalex.org/W6680140577"],"related_works":["https://openalex.org/W3149747767","https://openalex.org/W1536747792","https://openalex.org/W1982681402","https://openalex.org/W2192403599","https://openalex.org/W2366937720","https://openalex.org/W2163087802","https://openalex.org/W2155818328","https://openalex.org/W2121699558","https://openalex.org/W4244450895","https://openalex.org/W2074399518"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,22,71,124],"new":[4],"approach":[5,69],"of":[6,45,54,89,110,140,153,172],"band":[7,25,36,183],"selection":[8,26,37,184],"for":[9,29,42,51,83,112],"classifying":[10],"multiple":[11,159],"objects":[12],"in":[13,32,70],"hyperspectral":[14],"images.":[15],"Different":[16],"from":[17],"traditional":[18],"algorithms,":[19],"we":[20],"construct":[21],"semisupervised":[23,72,118,132],"pair-wise":[24],"(PWBS)":[27],"framework":[28],"this":[30],"task,":[31],"which":[33],"an":[34,66],"individual":[35],"process":[38,135],"is":[39,193],"performed":[40],"only":[41],"each":[43,55,87],"pair":[44,88],"classes.":[46],"First,":[47],"the":[48,93,100,120,131,143,149,154,170,190],"statistical":[49,95],"parameters":[50],"spectral":[52],"features":[53],"class,":[56],"including":[57],"mean":[58],"vectors":[59],"and":[60,78],"covariance":[61],"matrices,":[62],"are":[63,81,103,162],"estimated":[64,94],"by":[65,123],"expectation":[67,133],"maximization":[68,134],"learning":[73],"setting,":[74],"where":[75],"both":[76],"labeled":[77],"unlabeled":[79],"samples":[80,141],"employed":[82],"better":[84],"performance.":[85],"For":[86],"classes,":[90],"based":[91],"on":[92,142],"parameters,":[96],"Bhattacharyya":[97],"distances":[98],"between":[99],"two":[101],"classes":[102],"calculated":[104],"to":[105,136,147],"evaluate":[106,148],"all":[107,152],"possible":[108],"subsets":[109],"bands":[111],"classification.":[113],"Second,":[114],"as":[115],"our":[116,173,182],"proposed":[117,174],"framework,":[119],"PWBS":[121],"followed":[122],"binary":[125,155,160],"classifier":[126],"can":[127,186],"be":[128],"embedded":[129],"into":[130],"obtain":[137],"posterior":[138],"probabilities":[139],"selected":[144,150],"bands.":[145],"Finally,":[146],"bands,":[151],"decisions":[156],"obtained":[157],"with":[158],"classifiers":[161],"finally":[163],"fused":[164],"together.":[165],"Comparative":[166],"experimental":[167,177],"results":[168,178],"demonstrate":[169],"validity":[171],"algorithm.":[175],"The":[176],"also":[179],"prove":[180],"that":[181],"algorithm":[185],"perform":[187],"well":[188],"when":[189],"training":[191],"set":[192],"very":[194],"small.":[195]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}