{"id":"https://openalex.org/W4372266889","doi":"https://doi.org/10.1109/icassp49357.2023.10095232","title":"Robust Hyperspectral Anomaly Detection with Simultaneous Mixed Noise Removal via Constrained Convex Optimization","display_name":"Robust Hyperspectral Anomaly Detection with Simultaneous Mixed Noise Removal via Constrained Convex Optimization","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372266889","doi":"https://doi.org/10.1109/icassp49357.2023.10095232"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095232","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-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/A5019519134","display_name":"Koyo Sato","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Koyo Sato","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074225463","display_name":"Shunsuke Ono","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shunsuke Ono","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019519134"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":0.325,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59336912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"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":0.9879000186920166,"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":0.9625999927520752,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7377104759216309},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.69778972864151},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6845519542694092},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6374956965446472},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.6253811120986938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5635681748390198},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.5548862218856812},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.543236255645752},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.4984731674194336},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.43303436040878296},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41470763087272644},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3483487367630005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3394218683242798},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.2886039614677429},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27219855785369873},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2670970559120178},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.26019060611724854}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7377104759216309},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.69778972864151},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6845519542694092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6374956965446472},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.6253811120986938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5635681748390198},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.5548862218856812},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.543236255645752},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.4984731674194336},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.43303436040878296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41470763087272644},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3483487367630005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3394218683242798},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2886039614677429},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27219855785369873},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2670970559120178},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.26019060611724854},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095232","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095232","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1667895010","https://openalex.org/W1970099214","https://openalex.org/W1971358070","https://openalex.org/W1997201895","https://openalex.org/W2004491663","https://openalex.org/W2024288510","https://openalex.org/W2039596145","https://openalex.org/W2047870694","https://openalex.org/W2092663520","https://openalex.org/W2123031198","https://openalex.org/W2124267685","https://openalex.org/W2158449358","https://openalex.org/W2163886442","https://openalex.org/W2180180824","https://openalex.org/W2295576075","https://openalex.org/W2578004414","https://openalex.org/W2594827121","https://openalex.org/W2620976957","https://openalex.org/W2740976805","https://openalex.org/W2782517596","https://openalex.org/W2793218933","https://openalex.org/W2972480129","https://openalex.org/W3153686193","https://openalex.org/W3172624743","https://openalex.org/W3186256209","https://openalex.org/W3199351457","https://openalex.org/W4312342678","https://openalex.org/W4385819932"],"related_works":["https://openalex.org/W2986378528","https://openalex.org/W3178345791","https://openalex.org/W2949211747","https://openalex.org/W1550854977","https://openalex.org/W2092661960","https://openalex.org/W2588855097","https://openalex.org/W2162441712","https://openalex.org/W3005742472","https://openalex.org/W2087394828","https://openalex.org/W2161234930"],"abstract_inverted_index":{"Hyperspectral":[0],"(HS)":[1],"anomaly":[2,21,87,118],"detection":[3,22,72,88,163],"is":[4,41,49,54,173],"the":[5,29,71,132,148,157],"task":[6],"of":[7,31,70,74,96,123,139],"identifying":[8],"pixels":[9],"with":[10],"spectral":[11],"signatures":[12],"that":[13,51,107,156],"differ":[14],"significantly":[15],"from":[16],"surrounding":[17],"pixels.":[18],"Most":[19],"existing":[20,180],"methods":[23],"do":[24],"not":[25],"take":[26],"into":[27,113],"account":[28],"effect":[30],"noise":[32,53,178],"in":[33,67,166],"HS":[34,57,91,111,153],"images,":[35],"or":[36],"if":[37],"they":[38],"do,":[39],"it":[40,48],"only":[42],"Gaussian":[43],"noise.":[44,97,124],"In":[45,77],"practice,":[46],"however,":[47],"inevitable":[50],"non-Gaussian":[52],"superimposed":[55],"on":[56,135,152],"images":[58,92],"due":[59],"to":[60,84],"sensor":[61],"failure":[62],"and/or":[63],"calibration":[64],"errors,":[65],"resulting":[66],"considerable":[68],"degradation":[69],"performance":[73,164],"these":[75],"methods.":[76,181],"this":[78],"paper,":[79],"we":[80,99],"propose":[81],"a":[82,102,109,114,136,140],"method":[83,159],"achieve":[85],"robust":[86,176],"even":[89],"when":[90],"contain":[93],"various":[94],"types":[95,122],"Specifically,":[98],"newly":[100],"formulate":[101],"constrained":[103],"convex":[104],"optimization":[105],"problem":[106,133],"decomposes":[108],"given":[110],"image":[112],"background":[115],"part,":[116,119],"an":[117,128],"and":[120,168,171],"three":[121],"We":[125],"also":[126],"develop":[127],"efficient":[129],"solver":[130],"for":[131],"based":[134],"preconditioned":[137],"version":[138],"primal-dual":[141],"splitting":[142],"algorithm,":[143],"which":[144],"can":[145],"automatically":[146],"determine":[147],"appropriate":[149],"stepsizes.":[150],"Experiments":[151],"datasets":[154],"show":[155],"proposed":[158],"1)":[160],"achieves":[161],"state-of-the-art":[162],"both":[165],"noise-free":[167],"noisy":[169],"cases":[170],"2)":[172],"much":[174],"more":[175],"against":[177],"than":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}