{"id":"https://openalex.org/W2548364287","doi":"https://doi.org/10.1109/igarss.2016.7730714","title":"Spectral library pruning method in hyperspectral sparse unmixing","display_name":"Spectral library pruning method in hyperspectral sparse unmixing","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2548364287","doi":"https://doi.org/10.1109/igarss.2016.7730714","mag":"2548364287"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2016.7730714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7730714","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5025579103","display_name":"Honglei Lin","orcid":"https://orcid.org/0000-0002-9945-5050"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Honglei Lin","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101588866","display_name":"Xia Zhang","orcid":"https://orcid.org/0000-0002-4313-600X"},"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/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xia Zhang","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010433826","display_name":"Weichao Sun","orcid":"https://orcid.org/0000-0002-7511-5000"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weichao Sun","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":"53","issue":null,"first_page":"6561","last_page":"6564"},"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":0.9945999979972839,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9773291349411011},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6782416105270386},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.6525720953941345},{"id":"https://openalex.org/keywords/imaging-spectrometer","display_name":"Imaging spectrometer","score":0.6012895107269287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6007115840911865},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.548512876033783},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5286168456077576},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4686046838760376},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4558493196964264},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.44875699281692505},{"id":"https://openalex.org/keywords/mutual-coherence","display_name":"Mutual coherence","score":0.4389897584915161},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43081605434417725},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4195864200592041},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.3102473020553589},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21045300364494324},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09964564442634583},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08865460753440857},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06877642869949341}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9773291349411011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6782416105270386},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.6525720953941345},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.6012895107269287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6007115840911865},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.548512876033783},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5286168456077576},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4686046838760376},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4558493196964264},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.44875699281692505},{"id":"https://openalex.org/C45900066","wikidata":"https://www.wikidata.org/wiki/Q6944191","display_name":"Mutual coherence","level":3,"score":0.4389897584915161},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43081605434417725},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4195864200592041},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.3102473020553589},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21045300364494324},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09964564442634583},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08865460753440857},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06877642869949341},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2016.7730714","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7730714","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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":12,"referenced_works":["https://openalex.org/W1986530877","https://openalex.org/W2004207873","https://openalex.org/W2027878671","https://openalex.org/W2049418899","https://openalex.org/W2069231830","https://openalex.org/W2070424424","https://openalex.org/W2093985867","https://openalex.org/W2125298866","https://openalex.org/W2145554279","https://openalex.org/W2157321686","https://openalex.org/W2295820431","https://openalex.org/W4233760599"],"related_works":["https://openalex.org/W2746742660","https://openalex.org/W2761280200","https://openalex.org/W2171464537","https://openalex.org/W2119473622","https://openalex.org/W2138540356","https://openalex.org/W2799746630","https://openalex.org/W2561005839","https://openalex.org/W2079298906","https://openalex.org/W2000725643","https://openalex.org/W1529476013"],"abstract_inverted_index":{"Sparse":[0],"unmixing":[1,41],"algorithm":[2],"aims":[3],"at":[4],"finding":[5],"the":[6,29,37,49,64,77,93,102,106],"optimal":[7],"subset":[8],"of":[9,33,39,68],"signatures":[10],"from":[11,52],"a":[12,46],"spectral":[13,34,59,108],"library":[14,35,60,109],"to":[15,57,76],"best":[16],"model":[17],"each":[18],"pixel":[19],"in":[20],"hyperspectral":[21,53,79],"image":[22,54],"and":[23,66,81,95],"estimating":[24],"their":[25],"corresponding":[26],"abundance.":[27],"However,":[28],"high":[30],"mutual":[31],"coherence":[32],"limits":[36],"performance":[38],"sparse":[40,69],"algorithm.":[42],"In":[43],"this":[44],"paper,":[45],"method":[47,73],"referencing":[48],"extracted":[50],"information":[51],"was":[55,74],"managed":[56],"prune":[58],"(REiPSL)":[61],"for":[62],"improving":[63],"accuracy":[65,94],"efficiency":[67,96],"unmixing.":[70],"The":[71,89],"REiPSL":[72],"applied":[75],"simulated":[78],"data":[80],"Airborne":[82],"Visible":[83],"Infrared":[84],"Imaging":[85],"Spectrometer":[86],"(AVIRIS)":[87],"image.":[88],"experiments":[90],"show":[91],"that":[92],"are":[97],"improved":[98],"by":[99],"comparing":[100],"with":[101],"results":[103],"obtained":[104],"using":[105],"complete":[107],"directly.":[110]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}