{"id":"https://openalex.org/W2965282537","doi":"https://doi.org/10.3390/rs11151792","title":"A Novel Hyperspectral Endmember Extraction Algorithm Based on Online Robust Dictionary Learning","display_name":"A Novel Hyperspectral Endmember Extraction Algorithm Based on Online Robust Dictionary Learning","publication_year":2019,"publication_date":"2019-07-31","ids":{"openalex":"https://openalex.org/W2965282537","doi":"https://doi.org/10.3390/rs11151792","mag":"2965282537"},"language":"en","primary_location":{"id":"doi:10.3390/rs11151792","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11151792","pdf_url":"https://www.mdpi.com/2072-4292/11/15/1792/pdf?version=1564561293","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/2072-4292/11/15/1792/pdf?version=1564561293","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5083677290","display_name":"Song Xiaorui","orcid":"https://orcid.org/0000-0001-7438-4850"},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaorui Song","raw_affiliation_strings":["Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100293858","display_name":"Lingda Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingda Wu","raw_affiliation_strings":["Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China"],"affiliations":[{"raw_affiliation_string":"Science and Technology on Complex Electronic System Simulation Laboratory, Space Engineering University, Beijing 101416, China","institution_ids":["https://openalex.org/I4210148107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5083677290"],"corresponding_institution_ids":["https://openalex.org/I4210148107"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.9065,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.78672421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"11","issue":"15","first_page":"1792","last_page":"1792"},"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":0.9980999827384949,"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":0.992900013923645,"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/endmember","display_name":"Endmember","score":0.9204502105712891},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9087767601013184},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7522749900817871},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7054280638694763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6379121541976929},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5928544402122498}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9204502105712891},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9087767601013184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7522749900817871},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7054280638694763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6379121541976929},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5928544402122498},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs11151792","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11151792","pdf_url":"https://www.mdpi.com/2072-4292/11/15/1792/pdf?version=1564561293","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:6265f19d3b654c4ab24f1d8beaf3f249","is_oa":true,"landing_page_url":"https://doaj.org/article/6265f19d3b654c4ab24f1d8beaf3f249","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 11, Iss 15, p 1792 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs11151792","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11151792","pdf_url":"https://www.mdpi.com/2072-4292/11/15/1792/pdf?version=1564561293","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":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5249178904","display_name":null,"funder_award_id":"Grant No. 6","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6666755734","display_name":null,"funder_award_id":"61801513","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7726157001","display_name":null,"funder_award_id":"Grant No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965282537.pdf","grobid_xml":"https://content.openalex.org/works/W2965282537.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1531818640","https://openalex.org/W1755724306","https://openalex.org/W1899348529","https://openalex.org/W1964570608","https://openalex.org/W2000128031","https://openalex.org/W2021345820","https://openalex.org/W2063790512","https://openalex.org/W2070424424","https://openalex.org/W2076332129","https://openalex.org/W2093922090","https://openalex.org/W2095343758","https://openalex.org/W2095581126","https://openalex.org/W2101837437","https://openalex.org/W2106961167","https://openalex.org/W2114486983","https://openalex.org/W2125298866","https://openalex.org/W2131954031","https://openalex.org/W2142786738","https://openalex.org/W2157321686","https://openalex.org/W2163886442","https://openalex.org/W2324828044","https://openalex.org/W2334023959","https://openalex.org/W2344025572","https://openalex.org/W2741786247","https://openalex.org/W2802876668","https://openalex.org/W2894115892","https://openalex.org/W2894332515","https://openalex.org/W2898063830","https://openalex.org/W2902168190","https://openalex.org/W2903452964","https://openalex.org/W3101195009","https://openalex.org/W6679736339"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W3106536224","https://openalex.org/W2051769241","https://openalex.org/W2563324120","https://openalex.org/W2040756827","https://openalex.org/W2315521504","https://openalex.org/W2773863718"],"abstract_inverted_index":{"Due":[0],"to":[1,70,96],"the":[2,7,56,60,72,79,86,92,98,117,121],"sparsity":[3],"of":[4,55,59,75,85],"hyperspectral":[5,15,61,113],"images,":[6],"dictionary":[8,25,50,76,93],"learning":[9,26,94],"framework":[10],"has":[11],"been":[12],"applied":[13],"in":[14,31],"endmember":[16,20,43],"extraction.":[17],"However,":[18],"current":[19],"extraction":[21,44],"methods":[22],"based":[23,46],"on":[24,47],"are":[27],"not":[28],"robust":[29,49],"enough":[30],"noisy":[32,101],"environments.":[33],"To":[34],"solve":[35],"this":[36,38],"problem,":[37],"paper":[39],"proposes":[40],"a":[41,82],"novel":[42],"approach":[45],"online":[48,66],"learning,":[51],"termed":[52],"EEORDL.":[53],"Because":[54],"large":[57],"scale":[58],"image":[62],"(HSI)":[63],"data,":[64],"an":[65],"scheme":[67],"is":[68,89],"introduced":[69,90],"reduce":[71],"computational":[73],"time":[74],"learning.":[77],"In":[78],"proposed":[80,118],"algorithm,":[81],"new":[83],"form":[84],"objective":[87],"function":[88],"into":[91],"process":[95],"improve":[97],"robustness":[99],"for":[100,131],"HSI":[102],"data.":[103],"The":[104],"experimental":[105],"results,":[106],"conducted":[107],"with":[108],"both":[109],"synthetic":[110],"and":[111],"real-world":[112],"datasets,":[114],"illustrate":[115],"that":[116],"EEORDL":[119],"outperforms":[120],"state-of-the-art":[122],"approaches":[123],"under":[124],"different":[125],"signal-to-noise":[126],"ratio":[127],"(SNR)":[128],"conditions,":[129],"especially":[130],"high-level":[132],"noise.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-19T08:26:33.389920","created_date":"2025-10-10T00:00:00"}
