{"id":"https://openalex.org/W4312933485","doi":"https://doi.org/10.1109/igarss46834.2022.9883616","title":"Dual Spatial Weighted Sparse Hyperspectral Unmixing","display_name":"Dual Spatial Weighted Sparse Hyperspectral Unmixing","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312933485","doi":"https://doi.org/10.1109/igarss46834.2022.9883616"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883616","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 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/A5100723353","display_name":"Yonggang Chen","orcid":"https://orcid.org/0000-0002-9374-226X"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Jiangxi University of Water Resources and Electric Power","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yonggang Chen","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099","institution_ids":["https://openalex.org/I141103825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090973011","display_name":"Chengzhi Deng","orcid":"https://orcid.org/0000-0003-1605-7100"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Jiangxi University of Water Resources and Electric Power","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengzhi Deng","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099","institution_ids":["https://openalex.org/I141103825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002395584","display_name":"Shaoquan Zhang","orcid":"https://orcid.org/0000-0002-1454-9665"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Jiangxi University of Water Resources and Electric Power","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoquan Zhang","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099","institution_ids":["https://openalex.org/I141103825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373534","display_name":"Fan Li","orcid":"https://orcid.org/0000-0001-5077-8118"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Jiangxi University of Water Resources and Electric Power","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Li","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099","institution_ids":["https://openalex.org/I141103825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114526223","display_name":"Ningyuan Zhang","orcid":"https://orcid.org/0000-0002-1045-7392"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Jiangxi University of Water Resources and Electric Power","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ningyuan Zhang","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099","institution_ids":["https://openalex.org/I141103825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002188273","display_name":"Shengqian Wang","orcid":"https://orcid.org/0000-0001-9728-9995"},"institutions":[{"id":"https://openalex.org/I141103825","display_name":"Jiangxi University of Water Resources and Electric Power","ror":"https://ror.org/00avfj807","country_code":"CN","type":"education","lineage":["https://openalex.org/I141103825"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengqian Wang","raw_affiliation_strings":["Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology,Nanchang,China,330099","institution_ids":["https://openalex.org/I141103825"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2364,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51485608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1772","last_page":"1775"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.992900013923645,"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":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.81602543592453},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7118422985076904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6729713678359985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.635503888130188},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5842964053153992},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5729381442070007},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5634093880653381},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5083975195884705},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3413597047328949},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26487523317337036},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07734787464141846}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.81602543592453},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7118422985076904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6729713678359985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.635503888130188},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5842964053153992},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5729381442070007},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5634093880653381},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5083975195884705},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3413597047328949},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26487523317337036},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07734787464141846},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883616","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883616","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.800000011920929,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307827","display_name":"Crystal Technology & Industries","ror":"https://ror.org/04dckkc60"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1964570608","https://openalex.org/W2027878671","https://openalex.org/W2059976262","https://openalex.org/W2084252873","https://openalex.org/W2118246710","https://openalex.org/W2125298866","https://openalex.org/W2163886442","https://openalex.org/W2340706123","https://openalex.org/W2617737158","https://openalex.org/W2792167075","https://openalex.org/W3031385348","https://openalex.org/W3136776645","https://openalex.org/W3158091052","https://openalex.org/W4205264201","https://openalex.org/W6703976949"],"related_works":["https://openalex.org/W3034655717","https://openalex.org/W2090093270","https://openalex.org/W2783789044","https://openalex.org/W2139960062","https://openalex.org/W2737996023","https://openalex.org/W3159116204","https://openalex.org/W3186906619","https://openalex.org/W3168507287","https://openalex.org/W2909041182","https://openalex.org/W2765997769"],"abstract_inverted_index":{"Sparse":[0],"unmixing":[1,49,68,108,160,204,209],"is":[2,8,34,111,131],"a":[3,86,102,126,158],"semi-supervised":[4],"method":[5,174,187],"whose":[6],"pur-pose":[7],"to":[9,35,58,65,93,98,133,148],"find":[10],"the":[11,18,24,29,37,41,44,60,67,71,116,123,135,142,150,154,162,170,184],"best":[12,22],"subset":[13],"of":[14,40,120,137,153],"library":[15,20],"entries":[16],"from":[17],"spec-tral":[19],"that":[21,183],"model":[23,109],"image.":[25],"In":[26,96],"sparse":[27,48,107],"unmixing,":[28],"current":[30],"main":[31],"development":[32],"direction":[33,172],"incorporate":[36],"spatial":[38,53,56,61,105,143],"information":[39,119],"image":[42],"into":[43],"model.":[45],"Existing":[46],"spa-tial":[47],"algorithms":[50],"mainly":[51],"use":[52],"weights":[54],"or":[55,197],"regularization":[57],"characterize":[59],"correlation":[62],"between":[63],"pixels":[64],"improve":[66],"results.":[69],"For":[70,122],"complex":[72],"and":[73,201],"diverse":[74],"hyperspectral":[75,180],"data":[76,181],"in":[77,193],"reality,":[78],"most":[79],"al-gorithms":[80],"are":[81],"only":[82],"good":[83],"at":[84],"processing":[85],"single":[87],"scene,":[88],"which":[89,113],"brings":[90],"greater":[91],"challenges":[92],"their":[94],"practicality.":[95],"order":[97],"ad-dress":[99],"this":[100],"issue,":[101],"new":[103],"dual":[104],"weighted":[106],"(DSWSU)":[110],"proposed,":[112],"simultaneously":[114],"ex-ploits":[115],"spatially":[117],"homogeneous":[118],"images.":[121],"proposed":[124,163,185],"DSWSU,":[125],"pre-calculated":[127],"superpixel":[128],"weighting":[129,145],"factor":[130,146],"designed":[132],"mitigate":[134],"effect":[136],"noise":[138,199],"on":[139,178],"unmixing.":[140],"Meanwhile,":[141],"neighborhood":[144],"aims":[147],"promote":[149],"local":[151],"smoothness":[152],"abundance":[155,191],"maps.":[156],"As":[157],"simple":[159],"model,":[161],"DSWSU":[164,186],"can":[165,188],"be":[166],"quickly":[167],"solved":[168],"by":[169],"alternating":[171],"multiplier":[173],"(ADMM).":[175],"Experimental":[176],"results":[177,205],"simulated":[179],"indicate":[182],"achieve":[189],"accurate":[190],"estimation":[192],"various":[194],"scenarios":[195],"(low":[196],"high":[198],"interference),":[200],"obtain":[202],"better":[203],"than":[206],"other":[207],"state-of-the-art":[208],"algorithms.":[210]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
