{"id":"https://openalex.org/W2771221354","doi":"https://doi.org/10.1109/igarss.2017.8126936","title":"Sparse and low rank hyperspectral unmixing","display_name":"Sparse and low rank hyperspectral unmixing","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2771221354","doi":"https://doi.org/10.1109/igarss.2017.8126936","mag":"2771221354"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2017.8126936","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8126936","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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/A5079644472","display_name":"Jakob Sigur\u00f0sson","orcid":"https://orcid.org/0000-0002-4978-9722"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Jakob Sigurdsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069292094","display_name":"Magn\u00fas \u00d6. \u00dalfarsson","orcid":"https://orcid.org/0000-0002-0461-040X"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Magnus O. Ulfarsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008277487","display_name":"J\u00f3hannes R. Sveinsson","orcid":"https://orcid.org/0000-0001-6309-3126"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Johannes R. Sveinsson","raw_affiliation_strings":["Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical Eng., University of Iceland, Reykjavik, ICELAND","institution_ids":["https://openalex.org/I165368041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165368041"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.22507911,"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":"229","last_page":"232"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9976000189781189,"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":0.9185630083084106},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6261980533599854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6131497025489807},{"id":"https://openalex.org/keywords/robust-principal-component-analysis","display_name":"Robust principal component analysis","score":0.6121192574501038},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5886974930763245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5841338038444519},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5730303525924683},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5542994141578674},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5527302026748657},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5262997150421143},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5176670551300049},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.4558833837509155},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.45126038789749146},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4005105197429657},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35968807339668274},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.339285671710968},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3223947286605835},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10141035914421082}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9185630083084106},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6261980533599854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6131497025489807},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.6121192574501038},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5886974930763245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5841338038444519},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5730303525924683},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5542994141578674},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5527302026748657},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5262997150421143},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5176670551300049},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.4558833837509155},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.45126038789749146},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4005105197429657},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35968807339668274},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.339285671710968},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3223947286605835},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10141035914421082},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"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/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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/igarss.2017.8126936","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8126936","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 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":15,"referenced_works":["https://openalex.org/W1491012892","https://openalex.org/W1994040806","https://openalex.org/W2045983409","https://openalex.org/W2053061982","https://openalex.org/W2083138589","https://openalex.org/W2111031731","https://openalex.org/W2142635246","https://openalex.org/W2145012779","https://openalex.org/W2145962650","https://openalex.org/W2163886442","https://openalex.org/W2168175751","https://openalex.org/W2303627748","https://openalex.org/W2342750892","https://openalex.org/W2557168633","https://openalex.org/W4250857377"],"related_works":["https://openalex.org/W3037121946","https://openalex.org/W2991135868","https://openalex.org/W4387454008","https://openalex.org/W2594059414","https://openalex.org/W2962768932","https://openalex.org/W2798801347","https://openalex.org/W2523900061","https://openalex.org/W2737608760","https://openalex.org/W2507476065","https://openalex.org/W2060543695"],"abstract_inverted_index":{"In":[0],"this":[1,52],"paper,":[2],"hyperspectral":[3,96,128],"data":[4],"is":[5,24,40,73,91,121],"modeled":[6],"as":[7],"a":[8,11,14,25,74,124],"combination":[9],"of":[10,27,42,103],"sparse":[12,38,94],"component,":[13],"low":[15,21,68],"rank":[16,22,69],"component":[17,23,39],"and":[18,30,36,44,48,67,98,105],"noise.":[19,46],"The":[20,101,118],"product":[26],"the":[28,31,37,106,112],"endmembers":[29,104],"abundances":[32],"in":[33,51],"an":[34,86],"image,":[35],"composed":[41],"outliers":[43],"structured":[45,49],"Outliers":[47],"noise":[50],"context":[53],"are,":[54],"e.g.":[55],"band":[56],"specific":[57],"noise,":[58],"vertical":[59],"or":[60,63],"horizontal":[61],"artifacts":[62],"saturated":[64],"pixels.":[65],"Sparse":[66],"matrix":[70],"decomposition":[71],"(SLR)":[72],"method":[75],"that":[76],"has":[77],"recently":[78],"been":[79],"developed":[80,92],"for":[81],"estimating":[82],"those":[83],"components.":[84],"Here,":[85],"algorithm":[87,120],"based":[88],"on":[89],"\u21131SLR":[90],"using":[93,111,123],"blind":[95],"unmixing":[97],"soft":[99],"thresholding.":[100],"number":[102],"sparsity":[107],"parameters":[108],"are":[109],"selected":[110],"extended":[113],"Bayesian":[114],"information":[115],"criterion":[116],"(EBIC).":[117],"proposed":[119],"evaluated":[122],"real":[125],"remote":[126],"sensing":[127],"image.":[129]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}