{"id":"https://openalex.org/W2766336871","doi":"https://doi.org/10.1109/whispers.2014.8077558","title":"Spectrometer-driven spectral partitioning for hyperspectral image classification","display_name":"Spectrometer-driven spectral partitioning for hyperspectral image classification","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2766336871","doi":"https://doi.org/10.1109/whispers.2014.8077558","mag":"2766336871"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2014.8077558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2014.8077558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100362041","display_name":"Jun Li","orcid":"https://orcid.org/0000-0003-1613-9448"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["School of Geography and Planning, Sun Yat-sen University, Guangzhou, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Sun Yat-sen University, Guangzhou, P. R. China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100330566","display_name":"Yi Liu","orcid":"https://orcid.org/0000-0002-7168-9082"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Yi Liu","raw_affiliation_strings":["Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"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 State Administration of Surveying, Mapping, and Geoinformation of China, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory for Satellite Mapping Technology and Applications of State Administration of Surveying, Mapping, and Geoinformation of China, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I4210141849","https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055884274","display_name":"Mahdi Khodadadzadeh","orcid":"https://orcid.org/0000-0001-7899-738X"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Mahdi Khodadadzadeh","raw_affiliation_strings":["Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9807999730110168,"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/T13493","display_name":"Optical and Acousto-Optic Technologies","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9590568542480469},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.9070644378662109},{"id":"https://openalex.org/keywords/imaging-spectrometer","display_name":"Imaging spectrometer","score":0.8951324820518494},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.631467342376709},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5431922078132629},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5408613681793213},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5386012196540833},{"id":"https://openalex.org/keywords/imaging-spectroscopy","display_name":"Imaging spectroscopy","score":0.4789593517780304},{"id":"https://openalex.org/keywords/resampling","display_name":"Resampling","score":0.478546679019928},{"id":"https://openalex.org/keywords/spectral-signature","display_name":"Spectral signature","score":0.44130098819732666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3959874212741852},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35024145245552063},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.2727065086364746},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21571791172027588},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.19893112778663635},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12193259596824646}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9590568542480469},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.9070644378662109},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.8951324820518494},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.631467342376709},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5431922078132629},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5408613681793213},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5386012196540833},{"id":"https://openalex.org/C158479148","wikidata":"https://www.wikidata.org/wiki/Q609991","display_name":"Imaging spectroscopy","level":3,"score":0.4789593517780304},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.478546679019928},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.44130098819732666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3959874212741852},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35024145245552063},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2727065086364746},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21571791172027588},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.19893112778663635},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12193259596824646},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2014.8077558","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2014.8077558","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","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":9,"referenced_works":["https://openalex.org/W628438000","https://openalex.org/W1651266332","https://openalex.org/W1978149730","https://openalex.org/W2001298023","https://openalex.org/W2022470997","https://openalex.org/W2087263574","https://openalex.org/W2131697388","https://openalex.org/W2158400785","https://openalex.org/W2478493250"],"related_works":["https://openalex.org/W2332153559","https://openalex.org/W2047406830","https://openalex.org/W2028351632","https://openalex.org/W2799746630","https://openalex.org/W1995088959","https://openalex.org/W2370631906","https://openalex.org/W2505456708","https://openalex.org/W2555607644","https://openalex.org/W2113796989","https://openalex.org/W3023906449"],"abstract_inverted_index":{"Classification":[0],"is":[1,65,131,146],"an":[2,27],"important":[3],"and":[4,36,85,119,154],"widely":[5],"used":[6],"technique":[7],"for":[8,18,110],"remotely":[9],"sensed":[10],"hyperspectral":[11],"data":[12],"interpretation.":[13],"Although":[14],"most":[15],"techniques":[16],"developed":[17],"classification":[19,96,129,168],"assume":[20],"that":[21,159],"the":[22,47,57,74,102,106,112,137,160],"spectral":[23,76,113],"signatures":[24],"provided":[25],"by":[26,69,116],"imaging":[28,107],"spectrometer":[29,108],"can":[30],"be":[31,44],"interpreted":[32],"as":[33,133],"a":[34,94,134],"unique":[35],"continuous":[37],"signal,":[38],"in":[39,66,148,165,170],"practice":[40],"this":[41,90,149],"signal":[42],"may":[43],"obtained":[45,132,139],"after":[46],"combined":[48],"individual":[49,142],"responses":[50],"from":[51,140],"several":[52],"different":[53,71,123],"spectrometers.":[54],"For":[55],"instance,":[56],"Airborne":[58],"Visible":[59],"Infra-Red":[60],"Imaging":[61],"Spectrometer":[62],"(AVIRIS)":[63],"system":[64,109],"fact":[67],"formed":[68],"four":[70],"spectrometers,":[72],"covering":[73],"nominal":[75],"ranges":[77],"of":[78,105,136,167],"400-700":[79],"nm,":[80,82,84,87],"700-1300":[81],"1300-1900":[83],"1900-2500":[86],"respectively.":[88],"In":[89],"work,":[91],"we":[92],"propose":[93],"new":[95],"strategy":[97,162],"which":[98],"takes":[99],"into":[100,122],"account":[101],"physical":[103],"design":[104],"partitioning":[111],"bands":[114],"collected":[115],"each":[117,141],"spectrometer,":[118],"resampling":[120],"them":[121],"groups":[124],"or":[125],"partitions.":[126],"The":[127],"final":[128],"result":[130],"combination":[135],"results":[138,157],"partition.":[143],"This":[144],"concept":[145],"illustrated":[147],"work":[150],"using":[151],"AVIRIS":[152],"data,":[153],"our":[155],"experimental":[156],"indicate":[158],"proposed":[161],"provides":[163],"advantages":[164],"terms":[166],"accuracy,":[169],"particular,":[171],"when":[172],"very":[173],"limited":[174],"training":[175],"samples":[176],"are":[177],"available.":[178]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}