{"id":"https://openalex.org/W3207817117","doi":"https://doi.org/10.1109/tgrs.2021.3117765","title":"Component Decomposition Analysis for Hyperspectral Anomaly Detection","display_name":"Component Decomposition Analysis for Hyperspectral Anomaly Detection","publication_year":2021,"publication_date":"2021-10-20","ids":{"openalex":"https://openalex.org/W3207817117","doi":"https://doi.org/10.1109/tgrs.2021.3117765","mag":"3207817117"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3117765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3117765","pdf_url":null,"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":null,"license_id":null,"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":["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/A5028845261","display_name":"Shuhan Chen","orcid":"https://orcid.org/0000-0001-9996-0666"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhan Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9996-0666","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073412670","display_name":"Chein\u2010I Chang","orcid":"https://orcid.org/0000-0002-5450-4891"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]},{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Chein-I Chang","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","Remote Sensing Signal and Image Processing Laboratory, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-5450-4891","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]},{"raw_affiliation_string":"Remote Sensing Signal and Image Processing Laboratory, University of Maryland, Baltimore County (UMBC), Baltimore, MD, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101827905","display_name":"Xiaorun Li","orcid":"https://orcid.org/0000-0001-7611-845X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaorun Li","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7611-845X","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.6127,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.93548975,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"22"},"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":0.9864000082015991,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.6473859548568726},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5438973307609558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.466754674911499},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4302389919757843},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4002252519130707},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3616912364959717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32500168681144714},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.28924429416656494},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.128211110830307}],"concepts":[{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.6473859548568726},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5438973307609558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.466754674911499},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4302389919757843},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4002252519130707},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3616912364959717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32500168681144714},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.28924429416656494},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.128211110830307}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3117765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3117765","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W5731987","https://openalex.org/W2004491663","https://openalex.org/W2011147915","https://openalex.org/W2012113589","https://openalex.org/W2019502123","https://openalex.org/W2024288510","https://openalex.org/W2033888020","https://openalex.org/W2034259921","https://openalex.org/W2040078680","https://openalex.org/W2047870694","https://openalex.org/W2088518242","https://openalex.org/W2097900616","https://openalex.org/W2121789508","https://openalex.org/W2124463804","https://openalex.org/W2142552707","https://openalex.org/W2143690175","https://openalex.org/W2145554279","https://openalex.org/W2145962650","https://openalex.org/W2163547919","https://openalex.org/W2163599171","https://openalex.org/W2165447611","https://openalex.org/W2165755981","https://openalex.org/W2167708128","https://openalex.org/W2219019129","https://openalex.org/W2288752886","https://openalex.org/W2295576075","https://openalex.org/W2343117455","https://openalex.org/W2493273699","https://openalex.org/W2789516031","https://openalex.org/W2789806937","https://openalex.org/W2791725003","https://openalex.org/W2795739134","https://openalex.org/W2884073548","https://openalex.org/W2911876518","https://openalex.org/W2949079224","https://openalex.org/W2955133371","https://openalex.org/W2975506318","https://openalex.org/W3003955104","https://openalex.org/W3005109735","https://openalex.org/W3008839601","https://openalex.org/W3042747521","https://openalex.org/W3080792885","https://openalex.org/W3087883793","https://openalex.org/W3089477649","https://openalex.org/W3107126660","https://openalex.org/W3112037842","https://openalex.org/W3129037655","https://openalex.org/W3137199127","https://openalex.org/W3152468234","https://openalex.org/W3153686193","https://openalex.org/W3156696558","https://openalex.org/W3177111766","https://openalex.org/W3195212285","https://openalex.org/W4205778870","https://openalex.org/W4248253651"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W2531880140","https://openalex.org/W3205213561","https://openalex.org/W2051487156","https://openalex.org/W2963177394","https://openalex.org/W2073681303","https://openalex.org/W2024638892","https://openalex.org/W763418848","https://openalex.org/W1595229445"],"abstract_inverted_index":{"Low-rank":[0],"and":[1,144,204,219,271],"sparse":[2,38],"representation":[3],"(LRaSR)-based":[4],"approaches":[5],"have":[6],"been":[7],"widely":[8],"used":[9,70],"for":[10,71],"anomaly":[11,255],"detection":[12],"(AD).":[13],"Their":[14],"central":[15],"ideas":[16],"are":[17],"to":[18,27,35,50,185,251],"minimize":[19],"the":[20,23,37,52,68,187,195,230,240,268],"rank":[21],"of":[22,61,99,197,242],"low-rank":[24],"space":[25,92],"constrained":[26,53,191],"predetermined":[28],"values,":[29],"while":[30],"using":[31],"various":[32],"regularization":[33,62],"parameters":[34],"control":[36],"representation.":[39],"Three":[40],"key":[41],"issues":[42],"arise":[43],"from":[44,229],"LRaSR.":[45,177],"The":[46,55,64,258],"first":[47],"is":[48,57,67,246,264],"how":[49],"determine":[51],"rank.":[54],"second":[56],"an":[58],"appropriate":[59],"selection":[60],"parameters.":[63],"third":[65],"one":[66],"detector":[69,256],"AD.":[72,276],"This":[73],"article":[74],"presents":[75],"a":[76,90,95,168,220,253],"new":[77],"but":[78],"rather":[79],"simple":[80],"competing":[81],"model,":[82],"called":[83],"component":[84,141,164,170,182,238],"decomposition":[85,98,223],"analysis":[86,142,165,183],"(CDA)":[87],"which":[88],"represents":[89],"data":[91],"X":[93,102],"as":[94],"linear":[96],"orthogonal":[97],"three":[100],"components,":[101,129,152],"=":[103],"PC":[104,130],"<inline-formula":[105,113,122,131,145,154,198,205,232],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[106,114,123,132,146,155,199,206,233],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[107,115,124,133,147,156,200,207,234],"<tex-math":[108,116,125,134,148,157,201,208,235],"notation=\"LaTeX\">$^{{m}}":[109],"+$":[110,118],"</tex-math></inline-formula>":[111,119,127,136,150,159,203,210,237],"IC":[112,153,231],"notation=\"LaTeX\">$^{{j}}":[117],"N":[120],"with":[121],"notation=\"LaTeX\">${m}$":[126,202],"principal":[128,140],"notation=\"LaTeX\">$^{{m}}$":[135],",":[137,160],"generated":[138,161],"by":[139,162,215],"(PCA)":[143],"notation=\"LaTeX\">${j}$":[149,209],"independent":[151,163],"notation=\"LaTeX\">$^{{j}}$":[158,236],"(ICA)":[166],"plus":[167],"noise":[169],"N.":[171],"CDA":[172,179,250],"offers":[173],"several":[174],"advantages":[175],"over":[176],"First,":[178],"uses":[180],"well-known":[181],"techniques":[184],"decompose":[186],"dataset":[188],"without":[189],"solving":[190],"optimization":[192],"problems.":[193],"Second,":[194],"values":[196],"can":[211],"be":[212],"automatically":[213],"determined":[214],"virtual":[216],"dimensionality":[217],"(VD)":[218],"minimax-singular":[221],"value":[222],"(MX-SVD).":[224],"To":[225],"better":[226],"extract":[227],"anomalies":[228],"space,":[239],"concept":[241],"sparsity":[243],"cardinality":[244],"(SC)":[245],"further":[247],"incorporated":[248],"into":[249],"derive":[252],"CDASC":[254],"(CDASC-AD).":[257],"experimental":[259],"results":[260],"demonstrate":[261],"that":[262],"CDASC-AD":[263],"very":[265],"competitive":[266],"against":[267],"LRaSR-based":[269],"models":[270],"performs":[272],"well":[273],"in":[274],"hyperspectral":[275]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
