{"id":"https://openalex.org/W2766142280","doi":"https://doi.org/10.1109/whispers.2013.8080675","title":"Spectral unmixing-based post-processing for hyperspectral image classification","display_name":"Spectral unmixing-based post-processing for hyperspectral image classification","publication_year":2013,"publication_date":"2013-06-01","ids":{"openalex":"https://openalex.org/W2766142280","doi":"https://doi.org/10.1109/whispers.2013.8080675","mag":"2766142280"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2013.8080675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2013.8080675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 5th 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/A5078276287","display_name":"Inmaculada D\u00f3pido","orcid":null},"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":"Inmaculada Dopido","raw_affiliation_strings":["Department of Technology of Computers and Communications, University of Extremadura, Caceres, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, University of Extremadura, Caceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006623289","display_name":"Paolo Gamba","orcid":"https://orcid.org/0000-0002-9576-6337"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Gamba","raw_affiliation_strings":["Telecommunications and Remote Sensing Laboratory, University of Pavia, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Telecommunications and Remote Sensing Laboratory, University of Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]},{"author_position":"last","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, University of Extremadura, Caceres, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Technology of Computers and Communications, University of Extremadura, Caceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.38330215,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9883999824523926,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9864000082015991,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9638910293579102},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.7385212182998657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6894371509552002},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6730479001998901},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6572619676589966},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4573935270309448},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.44074711203575134},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23668524622917175},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.14330941438674927}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9638910293579102},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7385212182998657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6894371509552002},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6730479001998901},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6572619676589966},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4573935270309448},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.44074711203575134},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23668524622917175},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.14330941438674927}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2013.8080675","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2013.8080675","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 5th 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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W628438000","https://openalex.org/W1522547150","https://openalex.org/W1532610010","https://openalex.org/W1977556410","https://openalex.org/W2019985866","https://openalex.org/W2030476695","https://openalex.org/W2036745147","https://openalex.org/W2101365302","https://openalex.org/W2108917905","https://openalex.org/W2111975408","https://openalex.org/W2127062304","https://openalex.org/W2136625467","https://openalex.org/W2139987077","https://openalex.org/W2162480849","https://openalex.org/W2163886442","https://openalex.org/W2478493250","https://openalex.org/W3153297538","https://openalex.org/W6793955159"],"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/W2291489469","https://openalex.org/W2546503577"],"abstract_inverted_index":{"Spectral":[0],"unmixing":[1,25,66,90],"and":[2,23,50,91,93,152],"classification":[3,22,45,76,92,137],"have":[4,27],"been":[5,28],"widely":[6],"used":[7],"in":[8,67,97,150],"the":[9,44,61,71,75,87,118,130,136,142,145],"recent":[10],"literature":[11],"to":[12,42,69],"analyze":[13],"remotely":[14],"sensed":[15],"hyperspectral":[16,54,101,113],"data.":[17],"However,":[18],"possible":[19],"connections":[20],"between":[21,89],"spectral":[24,38,65],"concepts":[26],"rarely":[29],"investigated.":[30],"In":[31],"this":[32],"work,":[33],"we":[34],"propose":[35],"a":[36,111],"simple":[37],"unmixing-based":[39,132],"post-processing":[40],"method":[41,106],"improve":[43,135],"accuracies":[46],"provided":[47],"by":[48,117],"supervised":[49,82,151],"semi-supervised":[51,153],"techniques":[52,96],"for":[53,100,139],"image":[55],"classification.":[56],"The":[57,104],"proposed":[58,105,131],"approach":[59],"exploits":[60],"information":[62],"retrieved":[63],"with":[64],"order":[68],"complement":[70],"results":[72,127,138],"obtained":[73],"after":[74],"stage":[77],"(which":[78],"can":[79,134],"be":[80],"either":[81],"or":[83],"semi-supervised),":[84],"thus":[85],"bridging":[86],"gap":[88],"exploiting":[94],"both":[95],"synergistic":[98],"fashion":[99],"data":[102,114],"interpretation.":[103],"is":[107],"experimentally":[108],"validated":[109],"using":[110,155],"real":[112],"set":[115],"collected":[116],"Reflective":[119],"Optics":[120],"Spectrographic":[121],"Imaging":[122],"System":[123],"(ROSIS).":[124],"Our":[125],"experimental":[126],"indicate":[128],"that":[129],"preprocessing":[133],"some":[140],"of":[141],"classes,":[143],"particularly":[144],"most":[146],"highly":[147],"mixed":[148],"ones,":[149],"scenarios":[154],"limited":[156],"training":[157],"samples.":[158]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}