{"id":"https://openalex.org/W3176664940","doi":"https://doi.org/10.1109/tgrs.2022.3147423","title":"Sparse Linear Spectral Unmixing of Hyperspectral Images Using Expectation-Propagation","display_name":"Sparse Linear Spectral Unmixing of Hyperspectral Images Using Expectation-Propagation","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W3176664940","doi":"https://doi.org/10.1109/tgrs.2022.3147423","mag":"3176664940"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3147423","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3147423","pdf_url":"https://ieeexplore.ieee.org/ielx7/36/9633014/09695459.pdf","source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/36/9633014/09695459.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103608756","display_name":"Zeng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeng Li","raw_affiliation_strings":["School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067973917","display_name":"Yoann Altmann","orcid":"https://orcid.org/0000-0002-3177-9884"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yoann Altmann","raw_affiliation_strings":["School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333004","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0003-2306-8860"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010538525","display_name":"Stephen McLaughlin","orcid":"https://orcid.org/0000-0002-9558-8294"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Stephen Mclaughlin","raw_affiliation_strings":["School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, U.K","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054558832","display_name":"Susanto Rahardja","orcid":"https://orcid.org/0000-0003-0831-6934"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Susanto Rahardja","raw_affiliation_strings":["School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103608756"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":1.582,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.84381366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"13"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9869999885559082,"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/endmember","display_name":"Endmember","score":0.8931734561920166},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8797188997268677},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6253802180290222},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.604060709476471},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.49672991037368774},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4637942910194397},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4166383147239685},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4061998128890991},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38959938287734985},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2399522066116333},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09917470812797546}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.8931734561920166},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8797188997268677},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6253802180290222},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.604060709476471},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.49672991037368774},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4637942910194397},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4166383147239685},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4061998128890991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38959938287734985},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2399522066116333},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09917470812797546},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tgrs.2022.3147423","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3147423","pdf_url":"https://ieeexplore.ieee.org/ielx7/36/9633014/09695459.pdf","source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2106.09985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.09985","pdf_url":"https://arxiv.org/pdf/2106.09985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1109/tgrs.2022.3147423","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3147423","pdf_url":"https://ieeexplore.ieee.org/ielx7/36/9633014/09695459.pdf","source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1027852926","display_name":"Bayesian computation for low-photon imaging","funder_award_id":"EP/V006134/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1093520412","display_name":null,"funder_award_id":"Scholarship","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1361938442","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1934935867","display_name":null,"funder_award_id":"Engineering and Physical Sciences R","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G1951011414","display_name":"Bayesian computation for low-photon imaging","funder_award_id":"EP/V006177/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G2864483227","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320320005","funder_display_name":"Royal Academy of Engineering"},{"id":"https://openalex.org/G3574415789","display_name":null,"funder_award_id":"EP/V006177/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7764124984","display_name":null,"funder_award_id":"EP/V006134/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8145101974","display_name":null,"funder_award_id":"RF201617/16/31","funder_id":"https://openalex.org/F4320320005","funder_display_name":"Royal Academy of Engineering"},{"id":"https://openalex.org/G8589651859","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"},{"id":"https://openalex.org/G8602226179","display_name":null,"funder_award_id":"EP/T00097X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320320005","display_name":"Royal Academy of Engineering","ror":"https://ror.org/0526snb40"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3176664940.pdf","grobid_xml":"https://content.openalex.org/works/W3176664940.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W1555549210","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1923622064","https://openalex.org/W1934021597","https://openalex.org/W1937669826","https://openalex.org/W1964570608","https://openalex.org/W1964699659","https://openalex.org/W1972293418","https://openalex.org/W1974448798","https://openalex.org/W2005539942","https://openalex.org/W2015548667","https://openalex.org/W2027878671","https://openalex.org/W2032237655","https://openalex.org/W2049633694","https://openalex.org/W2070424424","https://openalex.org/W2081555128","https://openalex.org/W2084252873","https://openalex.org/W2084724634","https://openalex.org/W2092363223","https://openalex.org/W2101837437","https://openalex.org/W2114486983","https://openalex.org/W2125298866","https://openalex.org/W2125678373","https://openalex.org/W2127062304","https://openalex.org/W2144492104","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2258756789","https://openalex.org/W2295820431","https://openalex.org/W2540935574","https://openalex.org/W2604977491","https://openalex.org/W2617737158","https://openalex.org/W2738597227","https://openalex.org/W2741786247","https://openalex.org/W2770508708","https://openalex.org/W2774517539","https://openalex.org/W2792167075","https://openalex.org/W2801811332","https://openalex.org/W2902067790","https://openalex.org/W2921287797","https://openalex.org/W2939837652","https://openalex.org/W2952240579","https://openalex.org/W2963265857","https://openalex.org/W2963993380","https://openalex.org/W2967530387","https://openalex.org/W2983186010","https://openalex.org/W3012328093","https://openalex.org/W3024375667","https://openalex.org/W3091404876","https://openalex.org/W3105334813","https://openalex.org/W3154556605","https://openalex.org/W4212863985","https://openalex.org/W4233760599","https://openalex.org/W6633261909","https://openalex.org/W6640231202","https://openalex.org/W6694479622","https://openalex.org/W6746968042"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W2315521504","https://openalex.org/W3106536224","https://openalex.org/W2890371384","https://openalex.org/W2051769241","https://openalex.org/W2563324120","https://openalex.org/W2040756827"],"abstract_inverted_index":{"This":[0],"article":[1],"presents":[2],"a":[3,17,110],"novel":[4],"Bayesian":[5,130],"approach":[6],"for":[7,95],"hyperspectral":[8,168],"image":[9],"unmixing.":[10],"The":[11],"observed":[12],"pixels":[13],"are":[14,144],"modeled":[15],"by":[16,24],"linear":[18,179],"combination":[19],"of":[20,49,60,78,116,173],"material":[21],"signatures":[22],"weighted":[23],"their":[25],"corresponding":[26],"abundances.":[27],"A":[28],"spike-and-slab":[29],"abundance":[30],"prior":[31,41],"is":[32,43,154],"adopted":[33],"to":[34,45,88,138,156],"promote":[35],"sparse":[36],"mixtures":[37],"and":[38,82,149,166],"an":[39],"Ising":[40],"model":[42],"used":[44,155],"capture":[46],"spatial":[47],"correlation":[48],"the":[50,57,61,64,75,79,127,135,142,150,158,171,174],"mixture":[51],"support":[52],"across":[53],"pixels.":[54],"We":[55,68],"approximate":[56,129],"posterior":[58],"distribution":[59],"abundances":[62,143],"using":[63],"expectation-propagation":[65],"(EP)":[66],"method.":[67],"show":[69],"that":[70],"it":[71],"can":[72,106],"significantly":[73],"reduce":[74],"computational":[76],"complexity":[77],"unmixing":[80,180],"stage":[81],"meanwhile":[83],"provide":[84],"uncertainty":[85,96],"measures,":[86],"compared":[87],"expensive":[89],"Monte":[90],"Carlo":[91],"strategies":[92],"traditionally":[93],"considered":[94],"quantification.":[97],"Moreover,":[98],"many":[99],"variational":[100],"parameters":[101],"within":[102],"each":[103],"EP":[104],"factor":[105],"be":[107],"updated":[108],"in":[109],"parallel":[111],"manner,":[112],"which":[113],"enables":[114],"mapping":[115],"efficient":[117],"algorithmic":[118],"architectures":[119],"based":[120],"on":[121,163],"graphics":[122],"processing":[123],"units":[124],"(GPUs).":[125],"Under":[126],"same":[128],"framework,":[131],"we":[132],"then":[133],"extend":[134],"proposed":[136,175],"algorithm":[137,153],"semi-supervised":[139],"unmixing,":[140],"whereby":[141],"viewed":[145],"as":[146],"latent":[147],"variables":[148],"expectation-maximization":[151],"(EM)":[152],"refine":[157],"endmember":[159],"matrix.":[160],"Experimental":[161],"results":[162],"synthetic":[164],"data":[165,169],"real":[167],"illustrate":[170],"benefits":[172],"framework":[176],"over":[177],"state-of-art":[178],"methods.":[181]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}