{"id":"https://openalex.org/W2993951294","doi":"https://doi.org/10.1109/whispers.2019.8921375","title":"Fast Blind Hyperspectral Unmixing Based On Graph Laplacian","display_name":"Fast Blind Hyperspectral Unmixing Based On Graph Laplacian","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2993951294","doi":"https://doi.org/10.1109/whispers.2019.8921375","mag":"2993951294"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2019.8921375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2019.8921375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","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/A5066509235","display_name":"Jing Qin","orcid":"https://orcid.org/0000-0001-8630-2904"},"institutions":[{"id":"https://openalex.org/I143302722","display_name":"University of Kentucky","ror":"https://ror.org/02k3smh20","country_code":"US","type":"education","lineage":["https://openalex.org/I143302722"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jing Qin","raw_affiliation_strings":["Department of Mathematics, University of Kentucky, Lexington, KY"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Kentucky, Lexington, KY","institution_ids":["https://openalex.org/I143302722"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055567952","display_name":"Harlin Lee","orcid":"https://orcid.org/0000-0001-6128-9942"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harlin Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jocelyn T Chi","orcid":null},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jocelyn T Chi","raw_affiliation_strings":["Department of Statistics, North Carolina State University, Raleigh, NC"],"affiliations":[{"raw_affiliation_string":"Department of Statistics, North Carolina State University, Raleigh, NC","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062067602","display_name":"Yifei Lou","orcid":"https://orcid.org/0000-0003-1973-5704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifei Lou","raw_affiliation_strings":["Department of Mathematical Sciences, University of Texas, Dallas, TX"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Texas, Dallas, TX","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["CNRS, Grenoble INP, GIPSA-lab, University Grenoble Alpes, Grenoble, France"],"affiliations":[{"raw_affiliation_string":"CNRS, Grenoble INP, GIPSA-lab, University Grenoble Alpes, Grenoble, France","institution_ids":["https://openalex.org/I106785703","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I1294671590"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090707978","display_name":"Andrea L. Bertozzi","orcid":"https://orcid.org/0000-0003-0396-7391"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrea L. Bertozzi","raw_affiliation_strings":["Department of Mathematics, University of California, Los Angeles, CA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of California, Los Angeles, CA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5066509235"],"corresponding_institution_ids":["https://openalex.org/I143302722"],"apc_list":null,"apc_paid":null,"fwci":0.7252,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.7680427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9959999918937683,"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":0.9746000170707703,"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":0.9489592909812927},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.7891703844070435},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6913968324661255},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6365982294082642},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6140450835227966},{"id":"https://openalex.org/keywords/laplace-operator","display_name":"Laplace operator","score":0.5677257180213928},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.47791561484336853},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4413623809814453},{"id":"https://openalex.org/keywords/blind-signal-separation","display_name":"Blind signal separation","score":0.42112189531326294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38884395360946655},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3694854974746704},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27309006452560425},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2170589566230774}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9489592909812927},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.7891703844070435},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6913968324661255},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6365982294082642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6140450835227966},{"id":"https://openalex.org/C165700671","wikidata":"https://www.wikidata.org/wiki/Q203484","display_name":"Laplace operator","level":2,"score":0.5677257180213928},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.47791561484336853},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4413623809814453},{"id":"https://openalex.org/C120317606","wikidata":"https://www.wikidata.org/wiki/Q17105967","display_name":"Blind signal separation","level":3,"score":0.42112189531326294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38884395360946655},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3694854974746704},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27309006452560425},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2170589566230774},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.0},{"id":"https://openalex.org/C149530733","wikidata":"https://www.wikidata.org/wiki/Q5597091","display_name":"Graph power","level":4,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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":1,"locations":[{"id":"doi:10.1109/whispers.2019.8921375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2019.8921375","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1556650236","https://openalex.org/W1580188278","https://openalex.org/W1856231595","https://openalex.org/W1873031189","https://openalex.org/W1902027874","https://openalex.org/W1964570608","https://openalex.org/W2007680066","https://openalex.org/W2021080560","https://openalex.org/W2040325979","https://openalex.org/W2063069198","https://openalex.org/W2108119513","https://openalex.org/W2116810533","https://openalex.org/W2125298866","https://openalex.org/W2127062304","https://openalex.org/W2157321686","https://openalex.org/W2162957876","https://openalex.org/W2163886442","https://openalex.org/W2164278908","https://openalex.org/W2344025572","https://openalex.org/W2748318697","https://openalex.org/W2804275394","https://openalex.org/W2901918405","https://openalex.org/W4292363360","https://openalex.org/W6638914580","https://openalex.org/W6639119687","https://openalex.org/W6676321539","https://openalex.org/W6756463092"],"related_works":["https://openalex.org/W2188097034","https://openalex.org/W2029616478","https://openalex.org/W2570009360","https://openalex.org/W1717036717","https://openalex.org/W3004345458","https://openalex.org/W3016500305","https://openalex.org/W2051180862","https://openalex.org/W4244587941","https://openalex.org/W4200355242","https://openalex.org/W2287993572"],"abstract_inverted_index":{"Blind":[0],"hyperspectral":[1,21],"unmixing":[2,56],"is":[3],"a":[4,52,72,76,89,95],"challenging":[5],"problem":[6],"in":[7,105],"remote":[8],"sensing,":[9],"which":[10,36],"aims":[11],"to":[12,65,75],"infer":[13],"material":[14],"spectra":[15],"and":[16,69,109],"abundances":[17],"from":[18,27],"the":[19,43,62,81,102],"given":[20],"data.":[22],"Many":[23],"traditional":[24],"methods":[25],"suffer":[26],"poor":[28],"identification":[29],"of":[30,71,85,101,107],"materials":[31],"and/or":[32],"expensive":[33],"computational":[34],"costs,":[35],"can":[37],"be":[38],"partially":[39],"eased":[40],"by":[41],"trading":[42],"accuracy":[44,108],"with":[45],"efficiency.":[46,110],"In":[47,58],"this":[48],"work,":[49],"we":[50,60],"propose":[51],"fast":[53,90],"graph-based":[54],"blind":[55],"approach.":[57],"particular,":[59],"apply":[61],"Nystr\u00f6m":[63],"method":[64,84,104],"efficiently":[66],"approximate":[67],"eigenvalues":[68],"eigenvectors":[70],"matrix":[73],"corresponding":[74],"normalized":[77],"graph":[78],"Laplacian.":[79],"Then":[80],"alternating":[82],"direction":[83],"multipliers":[86],"(ADMM)":[87],"yields":[88],"numerical":[91],"algorithm.":[92],"Experiments":[93],"on":[94],"real":[96],"dataset":[97],"illustrate":[98],"great":[99],"potential":[100],"proposed":[103],"terms":[106]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
