{"id":"https://openalex.org/W4413267531","doi":"https://doi.org/10.1109/tgrs.2025.3593019","title":"Nonlocal and Deep Priors for Hyperspectral Anomaly Detection","display_name":"Nonlocal and Deep Priors for Hyperspectral Anomaly Detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4413267531","doi":"https://doi.org/10.1109/tgrs.2025.3593019"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3593019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3593019","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/A5052217040","display_name":"Longfei Ren","orcid":"https://orcid.org/0000-0002-0414-5114"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Longfei Ren","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0414-5114","affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005782558","display_name":"Degang Wang","orcid":"https://orcid.org/0000-0001-7524-1392"},"institutions":[{"id":"https://openalex.org/I31683504","display_name":"Beijing Forestry University","ror":"https://ror.org/04xv2pc41","country_code":"CN","type":"education","lineage":["https://openalex.org/I1327237609","https://openalex.org/I31683504","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degang Wang","raw_affiliation_strings":["School of Technology, the State Key Laboratory of Efficient Production of Forest Resources, and the Research Center for Biodiversity Intelligent Monitoring, Beijing Forestry University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7524-1392","affiliations":[{"raw_affiliation_string":"School of Technology, the State Key Laboratory of Efficient Production of Forest Resources, and the Research Center for Biodiversity Intelligent Monitoring, Beijing Forestry University, Beijing, China","institution_ids":["https://openalex.org/I31683504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066378186","display_name":"Lianru Gao","orcid":"https://orcid.org/0000-0003-3888-8124"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianru Gao","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3888-8124","affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100325515","display_name":"Minghua Wang","orcid":"https://orcid.org/0000-0001-5715-130X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghua Wang","raw_affiliation_strings":["Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, and Tianjin Key Laboratory of Intelligent Robotics (tjKLIR), Nankai University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-5715-130X","affiliations":[{"raw_affiliation_string":"Institute of Robotics and Automatic Information System (IRAIS), College of Artificial Intelligence, and Tianjin Key Laboratory of Intelligent Robotics (tjKLIR), Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100712730","display_name":"Min Huang","orcid":"https://orcid.org/0000-0001-6735-1612"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Huang","raw_affiliation_strings":["Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052217040"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210137199"],"apc_list":null,"apc_paid":null,"fwci":8.3779,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.97647208,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9138538837432861},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6102135181427002},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5199245810508728},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4644952118396759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4293111562728882},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4237651824951172},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3949313461780548},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.31189435720443726},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.18887624144554138}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9138538837432861},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6102135181427002},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5199245810508728},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4644952118396759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4293111562728882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4237651824951172},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3949313461780548},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.31189435720443726},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.18887624144554138}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3593019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3593019","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":[{"score":0.7099999785423279,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G2082383354","display_name":null,"funder_award_id":"62401546","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6156138116","display_name":null,"funder_award_id":"62201552","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1963408805","https://openalex.org/W1970201160","https://openalex.org/W2004491663","https://openalex.org/W2014311222","https://openalex.org/W2040078680","https://openalex.org/W2040895929","https://openalex.org/W2044810215","https://openalex.org/W2047870694","https://openalex.org/W2048695508","https://openalex.org/W2067897118","https://openalex.org/W2124463804","https://openalex.org/W2126607811","https://openalex.org/W2145962650","https://openalex.org/W2153663612","https://openalex.org/W2183325870","https://openalex.org/W2288752886","https://openalex.org/W2288987301","https://openalex.org/W2295576075","https://openalex.org/W2303627748","https://openalex.org/W2462946880","https://openalex.org/W2505029951","https://openalex.org/W2549107715","https://openalex.org/W2592141703","https://openalex.org/W2764207251","https://openalex.org/W2811215163","https://openalex.org/W2898121906","https://openalex.org/W2914736033","https://openalex.org/W2963299521","https://openalex.org/W2963814976","https://openalex.org/W2972480129","https://openalex.org/W2992919850","https://openalex.org/W3008839601","https://openalex.org/W3011440447","https://openalex.org/W3012209675","https://openalex.org/W3027585699","https://openalex.org/W3081108418","https://openalex.org/W3090929676","https://openalex.org/W3092426727","https://openalex.org/W3112037842","https://openalex.org/W3118914778","https://openalex.org/W3123098349","https://openalex.org/W3153686193","https://openalex.org/W3171243408","https://openalex.org/W3172689673","https://openalex.org/W3186256209","https://openalex.org/W3199351457","https://openalex.org/W3204653398","https://openalex.org/W4210330613","https://openalex.org/W4282929851","https://openalex.org/W4296210064","https://openalex.org/W4312659060","https://openalex.org/W4313524890","https://openalex.org/W4313590714","https://openalex.org/W4315750685","https://openalex.org/W4318707911","https://openalex.org/W4324290866","https://openalex.org/W4360993974","https://openalex.org/W4389104899","https://openalex.org/W4390494483","https://openalex.org/W4391956372","https://openalex.org/W4396870167","https://openalex.org/W4399394370","https://openalex.org/W4401360371","https://openalex.org/W4401507017","https://openalex.org/W4401705603","https://openalex.org/W4401878701","https://openalex.org/W4402665270","https://openalex.org/W4404239114","https://openalex.org/W4406280531","https://openalex.org/W4407566400","https://openalex.org/W4410204583","https://openalex.org/W4410536644","https://openalex.org/W6674855086"],"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/W2070598848","https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190"],"abstract_inverted_index":{"Hyperspectral":[0],"anomaly":[1,109],"detection":[2,110,177],"(HAD)":[3],"seeks":[4],"to":[5,92,102,137,152],"identify":[6],"targets":[7],"of":[8,79,116,124,147],"interest":[9],"within":[10,76],"hyperspectral":[11,163],"images":[12],"(HSIs)":[13],"without":[14],"requiring":[15],"prior":[16,87],"knowledge.":[17],"Recent":[18],"works":[19],"show":[20],"that":[21,63,166],"embedding":[22],"low-rank":[23,118],"attributes":[24],"in":[25,45,51],"the":[26,65,77,89,95,113,120,139,142,154,167],"HAD":[27],"task":[28],"can":[29],"yield":[30],"superior":[31,176],"results.":[32],"While":[33],"most":[34],"such":[35],"methods":[36],"focus":[37],"on":[38,158],"exploiting":[39],"global":[40,70],"or":[41],"local":[42],"geometrical":[43],"structures":[44],"HSIs,":[46],"largely":[47],"overlooking":[48],"similar":[49],"features":[50],"nonlocal":[52,61,66,90,104,117],"regions.":[53],"To":[54],"this":[55],"end,":[56],"we":[57,82],"propose":[58],"a":[59,84],"novel":[60],"framework":[62,91,170],"captures":[64],"self-similar":[67],"(NSS)":[68],"and":[69,105,119,161],"correlation":[71],"along":[72],"spectrum":[73],"(GCS)":[74],"priors":[75,107],"subspace":[78],"HSIs.":[80],"Then,":[81],"integrate":[83],"deep":[85,106,125],"denoiser":[86],"into":[88],"further":[93],"leverage":[94],"external":[96],"priors.":[97],"The":[98],"proposed":[99,168],"approach,":[100],"referred":[101],"as":[103],"for":[108],"(NLDPAD),":[111],"combines":[112],"structural":[114],"modeling":[115],"feature":[121],"extraction":[122],"capabilities":[123],"learning":[126],"(DL).":[127],"Furthermore,":[128],"an":[129],"efficient":[130],"alternating":[131,144],"minimization":[132],"(AM)":[133],"algorithm":[134],"was":[135,150],"developed":[136],"optimize":[138],"framework,":[140],"while":[141],"plug-and-play":[143],"direction":[145],"method":[146],"multipliers":[148],"(PnP-ADMM)":[149],"used":[151],"solve":[153],"subproblems.":[155],"Extensive":[156],"experiments":[157],"real":[159],"satellite":[160],"aerial":[162],"datasets":[164],"demonstrate":[165],"NLDPAD":[169],"significantly":[171],"outperforms":[172],"state-of-the-art":[173],"methods,":[174],"achieving":[175],"performance.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
