{"id":"https://openalex.org/W2770508708","doi":"https://doi.org/10.3390/rs9121224","title":"Joint Local Abundance Sparse Unmixing for Hyperspectral Images","display_name":"Joint Local Abundance Sparse Unmixing for Hyperspectral Images","publication_year":2017,"publication_date":"2017-11-27","ids":{"openalex":"https://openalex.org/W2770508708","doi":"https://doi.org/10.3390/rs9121224","mag":"2770508708"},"language":"en","primary_location":{"id":"doi:10.3390/rs9121224","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9121224","pdf_url":"https://www.mdpi.com/2072-4292/9/12/1224/pdf?version=1513225288","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/9/12/1224/pdf?version=1513225288","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057357858","display_name":"Mia Rizkinia","orcid":"https://orcid.org/0000-0003-3197-1611"},"institutions":[{"id":"https://openalex.org/I17056963","display_name":"The University of Kitakyushu","ror":"https://ror.org/03mfefw72","country_code":"JP","type":"education","lineage":["https://openalex.org/I17056963"]},{"id":"https://openalex.org/I29617571","display_name":"University of Indonesia","ror":"https://ror.org/0116zj450","country_code":"ID","type":"education","lineage":["https://openalex.org/I29617571"]}],"countries":["ID","JP"],"is_corresponding":true,"raw_author_name":"Mia Rizkinia","raw_affiliation_strings":["Faculty of Engineering, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia","Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Universitas Indonesia, Depok, Jawa Barat 16424, Indonesia","institution_ids":["https://openalex.org/I29617571"]},{"raw_affiliation_string":"Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan","institution_ids":["https://openalex.org/I17056963"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025207272","display_name":"Masahiro Okuda","orcid":"https://orcid.org/0000-0002-3245-2672"},"institutions":[{"id":"https://openalex.org/I17056963","display_name":"The University of Kitakyushu","ror":"https://ror.org/03mfefw72","country_code":"JP","type":"education","lineage":["https://openalex.org/I17056963"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Okuda","raw_affiliation_strings":["Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan","institution_ids":["https://openalex.org/I17056963"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057357858"],"corresponding_institution_ids":["https://openalex.org/I17056963","https://openalex.org/I29617571"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.3851,"has_fulltext":true,"cited_by_count":35,"citation_normalized_percentile":{"value":0.96170992,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"9","issue":"12","first_page":"1224","last_page":"1224"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9941999912261963,"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":0.9851999878883362,"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":0.9347886443138123},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.8941030502319336},{"id":"https://openalex.org/keywords/abundance-estimation","display_name":"Abundance estimation","score":0.6876224279403687},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6641213893890381},{"id":"https://openalex.org/keywords/abundance","display_name":"Abundance (ecology)","score":0.618696928024292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5650728344917297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49058833718299866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48340144753456116},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.41970372200012207},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.09040433168411255},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.08833342790603638},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06908619403839111}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9347886443138123},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.8941030502319336},{"id":"https://openalex.org/C2778514742","wikidata":"https://www.wikidata.org/wiki/Q16245026","display_name":"Abundance estimation","level":3,"score":0.6876224279403687},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6641213893890381},{"id":"https://openalex.org/C77077793","wikidata":"https://www.wikidata.org/wiki/Q336019","display_name":"Abundance (ecology)","level":2,"score":0.618696928024292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5650728344917297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49058833718299866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48340144753456116},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.41970372200012207},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.09040433168411255},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.08833342790603638},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06908619403839111},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs9121224","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9121224","pdf_url":"https://www.mdpi.com/2072-4292/9/12/1224/pdf?version=1513225288","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8d38e82bf4fa410584834170f4b1f63f","is_oa":true,"landing_page_url":"https://doaj.org/article/8d38e82bf4fa410584834170f4b1f63f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 9, Iss 12, p 1224 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/9/12/1224/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs9121224","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs9121224","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9121224","pdf_url":"https://www.mdpi.com/2072-4292/9/12/1224/pdf?version=1513225288","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1573579175","display_name":"\u30d7\u30ec\u30b9\u30c8\u30ec\u30b9\u3092\u4e0e\u3048\u305f\u4ea4\u53c9\u30ea\u30d6\u3092\u6709\u3059\u308b\u5e8a\u53c8\u306f\u58c1\u7528\u30b3\u30f3\u30af\u30ea\u30fc\u30c8\u7d44\u7acb\u7248","funder_award_id":"56047","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G2580193701","display_name":"\u539f\u4f53\u7167\u5c04\u306b\u304a\u3051\u308b\u7dda\u5de3\u6a2a\u65ad\u64ae\u5f71\u88c5\u7f6e\u306e\u8a66\u4f5c\u7814\u7a76(\u7d992\u5e74)","funder_award_id":"72310","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3459562248","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4874944895","display_name":null,"funder_award_id":"-in-Aid","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G518166858","display_name":"\u63a5\u6728\u91ce\u83dc\u306e\u990a\u5206\u5438\u53ce\u7279\u6027\u306b\u95a2\u3059\u308b\u7814\u7a76","funder_award_id":"456047","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5418018341","display_name":"\u65e5\u672c\u733f\u306e\u6bd4\u8f03\u884c\u52d5\u5b66\u7684\u533b\u5b66\u7684\u7814\u7a76","funder_award_id":"10003","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8891450116","display_name":null,"funder_award_id":"24560473","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320328515","display_name":"Lembaga Pengelola Dana Pendidikan","ror":null},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2770508708.pdf","grobid_xml":"https://content.openalex.org/works/W2770508708.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W5896900","https://openalex.org/W817041652","https://openalex.org/W1902027874","https://openalex.org/W1946620893","https://openalex.org/W1964570608","https://openalex.org/W1965340435","https://openalex.org/W1976391658","https://openalex.org/W1981939910","https://openalex.org/W1994040806","https://openalex.org/W1997677658","https://openalex.org/W2004207873","https://openalex.org/W2009576740","https://openalex.org/W2019149505","https://openalex.org/W2027878671","https://openalex.org/W2044496796","https://openalex.org/W2053514113","https://openalex.org/W2069231830","https://openalex.org/W2084252873","https://openalex.org/W2099703033","https://openalex.org/W2108517747","https://openalex.org/W2122976738","https://openalex.org/W2125298866","https://openalex.org/W2126527280","https://openalex.org/W2128090514","https://openalex.org/W2129131372","https://openalex.org/W2144492104","https://openalex.org/W2156401956","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2166864699","https://openalex.org/W2169466597","https://openalex.org/W2277068403","https://openalex.org/W2293524743","https://openalex.org/W2295820431","https://openalex.org/W2323672905","https://openalex.org/W2345595902","https://openalex.org/W2412830023","https://openalex.org/W2418010766","https://openalex.org/W2467741384","https://openalex.org/W2528961482","https://openalex.org/W2549553889","https://openalex.org/W2576295610","https://openalex.org/W2617100983","https://openalex.org/W2632329989","https://openalex.org/W2739611913","https://openalex.org/W2765202580","https://openalex.org/W2949464013","https://openalex.org/W3099180803","https://openalex.org/W4233760599","https://openalex.org/W6676376460","https://openalex.org/W6745193812"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W3106536224","https://openalex.org/W2891033441","https://openalex.org/W1988881499","https://openalex.org/W2006559622","https://openalex.org/W1990914742","https://openalex.org/W2081682213","https://openalex.org/W4379116984","https://openalex.org/W240039221","https://openalex.org/W2127934268"],"abstract_inverted_index":{"Sparse":[0],"unmixing":[1,87],"is":[2,44,76,130],"widely":[3],"used":[4],"for":[5,114,143,152],"hyperspectral":[6,23,156],"imagery":[7],"to":[8,46,84,110],"estimate":[9],"the":[10,27,47,50,54,61,64,69,80,85,101,107,111,126,133,140,163,181],"optimal":[11],"fraction":[12],"(abundance)":[13],"of":[14,21,63,68,117,165],"materials":[15],"contained":[16],"in":[17,40,53,66],"mixed":[18],"pixels":[19],"(endmembers)":[20],"a":[22,33],"scene,":[24],"by":[25,105],"considering":[26,79],"abundance":[28,31,65,83,104,112,120,128],"sparsity.":[29],"This":[30,43,59],"has":[32],"unique":[34],"property,":[35],"i.e.,":[36],"high":[37],"spatial":[38,118,146],"correlation":[39],"local":[41,82,103,115,127],"regions.":[42],"due":[45],"fact":[48],"that":[49,78,99,171],"endmembers":[51],"existing":[52],"region":[55],"are":[56],"highly":[57],"correlated.":[58],"implies":[60],"low-rankness":[62],"terms":[67],"endmember.":[70],"From":[71],"this":[72,93],"prior":[73],"knowledge,":[74],"it":[75],"expected":[77],"low-rank":[81,102],"sparse":[86],"problem":[88],"improves":[89],"estimation":[90],"performance.":[91],"In":[92,122],"study,":[94],"we":[95],"propose":[96],"an":[97],"algorithm":[98,173],"exploits":[100],"applying":[106],"nuclear":[108],"norm":[109,138],"matrix":[113],"regions":[116],"and":[119,139,145,154,161,177],"domains.":[121],"our":[123,172],"optimization":[124],"problem,":[125],"regularizer":[129],"collaborated":[131],"with":[132,160],"L":[134],"2":[135],",":[136],"1":[137],"total":[141],"variation":[142],"sparsity":[144],"information,":[147],"respectively.":[148],"We":[149],"conducted":[150],"experiments":[151,169],"real":[153],"simulated":[155],"data":[157],"sets":[158],"assuming":[159],"without":[162],"presence":[164],"pure":[166],"pixels.":[167],"The":[168],"showed":[170],"yields":[174],"competitive":[175],"results":[176],"performs":[178],"better":[179],"than":[180],"conventional":[182],"algorithms.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":6}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
