{"id":"https://openalex.org/W3138448509","doi":"https://doi.org/10.1109/lgrs.2021.3063252","title":"Hyperspectral Anomaly Detection via <i>S</i> <sub>1/2</sub> Regularized Low Rank Representation","display_name":"Hyperspectral Anomaly Detection via <i>S</i> <sub>1/2</sub> Regularized Low Rank Representation","publication_year":2021,"publication_date":"2021-03-15","ids":{"openalex":"https://openalex.org/W3138448509","doi":"https://doi.org/10.1109/lgrs.2021.3063252","mag":"3138448509"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2021.3063252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3063252","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5100432452","display_name":"Jingyu Wang","orcid":"https://orcid.org/0000-0001-7017-1938"},"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":"Jingyu Wang","raw_affiliation_strings":["School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","School of Astronautics, Northwestern Polytechnical University, Xi'an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-7017-1938","affiliations":[{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101911546","display_name":"Pengfei Huang","orcid":"https://orcid.org/0000-0003-4092-2918"},"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":"Pengfei Huang","raw_affiliation_strings":["School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","School of Astronautics, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0003-4092-2918","affiliations":[{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365775","display_name":"Ke Zhang","orcid":"https://orcid.org/0009-0008-7558-2275"},"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":"Ke Zhang","raw_affiliation_strings":["School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","School of Astronautics, Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Astronautics, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341321","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-7028-4956"},"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":"Qi Wang","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0002-7028-4956","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":0.2492,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55414361,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"19","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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9800000190734863,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9599000215530396,"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":0.8229011297225952},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5663052797317505},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5131245255470276},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.5111110806465149},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5097751021385193},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5012555122375488},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.4829651415348053},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4401851296424866},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4317959249019623},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.41797682642936707},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38476744294166565},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37355107069015503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3681962490081787},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.27928799390792847},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.13848385214805603},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.11117634177207947}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8229011297225952},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5663052797317505},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5131245255470276},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.5111110806465149},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5097751021385193},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5012555122375488},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.4829651415348053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4401851296424866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4317959249019623},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.41797682642936707},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38476744294166565},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37355107069015503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3681962490081787},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.27928799390792847},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.13848385214805603},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.11117634177207947},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/lgrs.2021.3063252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3063252","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1530037185","display_name":null,"funder_award_id":"61976179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2508657349","display_name":null,"funder_award_id":"3102019HTXM005","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3757765813","display_name":null,"funder_award_id":"3102017HQZZ003","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4347962660","display_name":null,"funder_award_id":"61502391","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6535508763","display_name":null,"funder_award_id":"3102019HTXS001","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1970099214","https://openalex.org/W1978484841","https://openalex.org/W1997201895","https://openalex.org/W2004491663","https://openalex.org/W2024288510","https://openalex.org/W2042442393","https://openalex.org/W2047870694","https://openalex.org/W2056201402","https://openalex.org/W2124463804","https://openalex.org/W2295576075","https://openalex.org/W2588599464","https://openalex.org/W2605100742","https://openalex.org/W2740101263","https://openalex.org/W2741379673","https://openalex.org/W2800662010","https://openalex.org/W2801018674","https://openalex.org/W2884073548","https://openalex.org/W2898121906","https://openalex.org/W2901756546","https://openalex.org/W2914429466","https://openalex.org/W2959891261","https://openalex.org/W2978534540","https://openalex.org/W2981073809","https://openalex.org/W2987226824","https://openalex.org/W2991283753","https://openalex.org/W3010770313","https://openalex.org/W3023241480","https://openalex.org/W3027629341"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W4313014865","https://openalex.org/W2969683494"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1],"has":[2,23,158],"been":[3,24,159],"drawing":[4],"a":[5,36,48,55,65,145],"great":[6,37],"deal":[7],"of":[8,12,39,58,85],"attention":[9],"by":[10],"virtue":[11],"its":[13],"practicability":[14],"among":[15],"the":[16,87,105,111,128,132,135,153,168],"hyperspectral":[17,31,90],"research":[18],"area.":[19],"Low-rank":[20],"representation":[21],"(LRR)":[22],"widely":[25],"employed":[26],"to":[27,54,103,109,126,151],"detect":[28],"anomalies":[29],"from":[30,42],"imagery":[32],"(HSI)":[33],"effectively":[34],"while":[35],"number":[38],"methods":[40],"derived":[41],"LRR":[43,78],"replace":[44],"rank":[45,112],"function":[46],"with":[47,81],"nuclear":[49,107],"norm,":[50],"which":[51],"gives":[52],"rise":[53],"certain":[56],"amount":[57],"error.":[59],"In":[60],"this":[61],"letter,":[62],"we":[63],"propose":[64],"Schatten":[66],"1/2":[67],"quasi-norm":[68],"(":[69],"<inline-formula":[70,94],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[71,95],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[72,96],"<tex-math":[73,97],"notation=\"LaTeX\">$S_{1/2}$":[74,98],"</tex-math></inline-formula>":[75,99],")":[76],"regularized":[77],"(SRLRR)":[79],"method":[80,142,157],"an":[82,115],"improved":[83,116],"algorithm":[84,119,137],"establishing":[86],"dictionary":[88,117],"for":[89],"anomaly":[91],"detection.":[92],"First,":[93],"regularization":[100],"is":[101,124,149],"proposed":[102],"substitute":[104],"initial":[106],"norm":[108],"approximate":[110],"function.":[113],"Second,":[114],"construction":[118],"based":[120],"on":[121,161],"K-Means++":[122],"clustering":[123],"presented":[125],"integrate":[127],"model":[129],"and":[130,166],"improve":[131],"performance.":[133,170],"Finally,":[134],"optimization":[136],"through":[138],"alternating":[139],"direction":[140],"multiplier":[141],"(ADMM)":[143],"incorporating":[144],"half":[146],"threshold":[147],"operator":[148],"introduced":[150],"attain":[152],"eventual":[154],"results.":[155],"Our":[156],"testified":[160],"three":[162],"typical":[163],"data":[164],"sets":[165],"demonstrates":[167],"eminent":[169]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
