{"id":"https://openalex.org/W4214806231","doi":"https://doi.org/10.1109/tnnls.2022.3152252","title":"Hyperspectral Anomaly Detection With Tensor Average Rank and Piecewise Smoothness Constraints","display_name":"Hyperspectral Anomaly Detection With Tensor Average Rank and Piecewise Smoothness Constraints","publication_year":2022,"publication_date":"2022-03-04","ids":{"openalex":"https://openalex.org/W4214806231","doi":"https://doi.org/10.1109/tnnls.2022.3152252","pmid":"https://pubmed.ncbi.nlm.nih.gov/35245203"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3152252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3152252","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Siyu Sun","orcid":"https://orcid.org/0000-0003-4623-2192"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Siyu Sun","raw_affiliation_strings":["Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jun Liu","orcid":"https://orcid.org/0000-0002-7193-0622"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Liu","raw_affiliation_strings":["Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xun Chen","orcid":"https://orcid.org/0000-0002-4922-8116"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xun Chen","raw_affiliation_strings":["Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":null,"display_name":"Hongbin Li","orcid":"https://orcid.org/0000-0003-1453-847X"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongbin Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA","institution_ids":["https://openalex.org/I108468826"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":7.5717,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.97711531,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"34","issue":"11","first_page":"8679","last_page":"8692"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9898999929428101,"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":0.9898999929428101,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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":0.8097000122070312},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7405999898910522},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6488999724388123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6097000241279602},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.5740000009536743},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.5228999853134155},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4869000017642975},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.4814999997615814},{"id":"https://openalex.org/keywords/matrix-norm","display_name":"Matrix norm","score":0.43459999561309814},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4153999984264374}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8097000122070312},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7405999898910522},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6488999724388123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6097000241279602},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.5740000009536743},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.5228999853134155},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4936999976634979},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4779999852180481},{"id":"https://openalex.org/C92207270","wikidata":"https://www.wikidata.org/wiki/Q939253","display_name":"Matrix norm","level":3,"score":0.43459999561309814},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.426800012588501},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4154999852180481},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4153999984264374},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.3952000141143799},{"id":"https://openalex.org/C78168278","wikidata":"https://www.wikidata.org/wiki/Q5227269","display_name":"Data cube","level":2,"score":0.39010000228881836},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C2986737658","wikidata":"https://www.wikidata.org/wiki/Q30103009","display_name":"Tensor decomposition","level":3,"score":0.3582000136375427},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.30230000615119934},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2831999957561493},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C136272165","wikidata":"https://www.wikidata.org/wiki/Q4048889","display_name":"Singular spectrum analysis","level":3,"score":0.2786000072956085},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.27129998803138733},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26930001378059387},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.25940001010894775}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3152252","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3152252","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35245203","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35245203","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1527336764","display_name":null,"funder_award_id":"CX2100060053","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G1970520617","display_name":null,"funder_award_id":"61922075","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3580731644","display_name":null,"funder_award_id":"61871469","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7394983629","display_name":null,"funder_award_id":"61922013","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"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1970099214","https://openalex.org/W1997201895","https://openalex.org/W2004491663","https://openalex.org/W2030927653","https://openalex.org/W2040078680","https://openalex.org/W2043571470","https://openalex.org/W2047870694","https://openalex.org/W2048578762","https://openalex.org/W2067782748","https://openalex.org/W2067897118","https://openalex.org/W2118246710","https://openalex.org/W2121789508","https://openalex.org/W2124463804","https://openalex.org/W2145962650","https://openalex.org/W2151665594","https://openalex.org/W2160547390","https://openalex.org/W2167320870","https://openalex.org/W2288752886","https://openalex.org/W2292803159","https://openalex.org/W2292987679","https://openalex.org/W2295576075","https://openalex.org/W2343117455","https://openalex.org/W2424277038","https://openalex.org/W2497075055","https://openalex.org/W2547840382","https://openalex.org/W2610484101","https://openalex.org/W2625541168","https://openalex.org/W2740976805","https://openalex.org/W2762599734","https://openalex.org/W2767039949","https://openalex.org/W2791928749","https://openalex.org/W2796629918","https://openalex.org/W2808979303","https://openalex.org/W2811215163","https://openalex.org/W2887843685","https://openalex.org/W2900199428","https://openalex.org/W2922177059","https://openalex.org/W2951401720","https://openalex.org/W2954497554","https://openalex.org/W2963885538","https://openalex.org/W2972301798","https://openalex.org/W2972480129","https://openalex.org/W2990162903","https://openalex.org/W2997011911","https://openalex.org/W2998493545","https://openalex.org/W2998940023","https://openalex.org/W2999694498","https://openalex.org/W3008839601","https://openalex.org/W3017506038","https://openalex.org/W3021083191","https://openalex.org/W3023241480","https://openalex.org/W3026587394","https://openalex.org/W3028138626","https://openalex.org/W3030694258","https://openalex.org/W3038851053","https://openalex.org/W3042747521","https://openalex.org/W3087782035","https://openalex.org/W3087883793","https://openalex.org/W3118889207","https://openalex.org/W3158390871","https://openalex.org/W3195044646","https://openalex.org/W6681016373","https://openalex.org/W6722444669","https://openalex.org/W6745590288","https://openalex.org/W6787044350","https://openalex.org/W6793904778","https://openalex.org/W6795875694","https://openalex.org/W6796067264"],"related_works":[],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,33,68,78,260],"in":[2,10,67,128],"hyperspectral":[3,246],"images":[4],"(HSIs)":[5],"has":[6],"attracted":[7],"considerable":[8,65],"interest":[9],"the":[11,30,36,51,56,84,88,94,107,113,123,130,136,141,150,154,157,164,174,177,181,184,195,219,234,249,252],"remote-sensing":[12],"domain,":[13],"which":[14,49],"aims":[15],"to":[16,40,64,121,149,162,172,179,221],"identify":[17],"pixels":[18,57,224],"with":[19,256],"different":[20],"spectral":[21,47,131,204],"and":[22,58,102,132,206,237],"spatial":[23,53,133,207],"features":[24],"from":[25,183],"their":[26,59,203],"surroundings.":[27],"Most":[28],"of":[29,45,87,135,167,176,251],"existing":[31,127],"anomaly":[32,77,104,155,182,259],"methods":[34],"convert":[35],"3-D":[37,95],"data":[38,97,197],"cube":[39],"a":[41,75,99,188,212],"2-D":[42],"matrix":[43],"composed":[44],"independent":[46],"vectors,":[48],"destroys":[50],"intrinsic":[52],"correlation":[54],"between":[55],"surrounding":[60],"pixels,":[61],"thus":[62],"leading":[63],"degradation":[66],"performance.":[69],"In":[70,139,170],"this":[71],"article,":[72],"we":[73,186,210],"develop":[74,211],"tensor-based":[76],"algorithm":[79,178],"that":[80],"can":[81,231],"effectively":[82,232],"preserve":[83],"spatial-spectral":[85],"information":[86],"original":[89],"data.":[90],"We":[91,192],"first":[92,193],"separate":[93],"HSI":[96,196],"into":[98,198],"background":[100,137,190,229,235],"tensor":[101,108,114],"an":[103],"tensor.":[105,138],"Then":[106,209],"nuclear":[109],"norm":[110,159],"based":[111,217],"on":[112,218],"singular":[115],"value":[116],"decomposition":[117],"(SVD)":[118],"is":[119,146,160],"exploited":[120,161],"characterize":[122],"global":[124],"low":[125],"rank":[126],"both":[129],"directions":[134],"addition,":[140],"total":[142],"variation":[143],"(TV)":[144],"regularization":[145],"incorporated":[147],"due":[148],"piecewise":[151],"smoothness.":[152],"For":[153],"component,":[156],"l<sub>2.1</sub>":[158],"promote":[163],"group":[165],"sparsity":[166],"anomalous":[168],"pixels.":[169],"order":[171],"improve":[173],"ability":[175],"distinguish":[180],"background,":[185],"design":[187],"robust":[189],"dictionary.":[191],"split":[194],"local":[199],"clusters":[200],"by":[201],"leveraging":[202],"similarity":[205],"distance.":[208],"simple":[213],"but":[214],"effective":[215],"way":[216],"SVD":[220],"select":[222],"representative":[223],"as":[225],"atoms.":[226],"The":[227],"constructed":[228],"dictionary":[230],"represent":[233],"materials":[236],"eliminate":[238],"anomalies.":[239],"Experimental":[240],"results":[241],"obtained":[242],"using":[243],"several":[244],"real":[245],"datasets":[247],"demonstrate":[248],"superiority":[250],"proposed":[253],"method":[254],"compared":[255],"some":[257],"state-of-the-art":[258],"algorithms.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":26},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2022-03-05T00:00:00"}