{"id":"https://openalex.org/W2044941312","doi":"https://doi.org/10.1109/whispers.2011.6080971","title":"Evaluation of the sub-pixel performance of anomaly detectors","display_name":"Evaluation of the sub-pixel performance of anomaly detectors","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2044941312","doi":"https://doi.org/10.1109/whispers.2011.6080971","mag":"2044941312"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2011.6080971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2011.6080971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5075271216","display_name":"Dirk Borghys","orcid":"https://orcid.org/0000-0002-4105-5214"},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"D. Borghys","raw_affiliation_strings":["Royal Military Academy Signal & Image Centre, Brussels, Belgium","Royal Military Academy, Signal and Image Centre, Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Royal Military Academy Signal & Image Centre, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]},{"raw_affiliation_string":"Royal Military Academy, Signal and Image Centre, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038825428","display_name":"Christiaan Perneel","orcid":null},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"C. Perneel","raw_affiliation_strings":["Royal Military Academy Signal & Image Centre, Brussels, Belgium","Royal Military Academy, Signal and Image Centre, Brussels, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Royal Military Academy Signal & Image Centre, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]},{"raw_affiliation_string":"Royal Military Academy, Signal and Image Centre, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075223740","display_name":"V\u00e9ronique Achard","orcid":"https://orcid.org/0000-0002-2344-8161"},"institutions":[{"id":"https://openalex.org/I193033237","display_name":"Institut Sup\u00e9rieur de l'A\u00e9ronautique et de l'Espace (ISAE-SUPAERO)","ror":"https://ror.org/04gyj6s21","country_code":"FR","type":"education","lineage":["https://openalex.org/I193033237"]},{"id":"https://openalex.org/I2801658355","display_name":"Office National d'\u00c9tudes et de Recherches A\u00e9rospatiales","ror":"https://ror.org/005y2ap84","country_code":"FR","type":"facility","lineage":["https://openalex.org/I2801658355"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"V. Achard","raw_affiliation_strings":["French AeroSpace Laboratory, ONERA, Toulouse, France","ONERA, French Aerospace Lab, Toulouse, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"French AeroSpace Laboratory, ONERA, Toulouse, France","institution_ids":["https://openalex.org/I193033237","https://openalex.org/I2801658355"]},{"raw_affiliation_string":"ONERA, French Aerospace Lab, Toulouse, France","institution_ids":["https://openalex.org/I2801658355"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021240779","display_name":"Ingebj\u00f8rg K\u00e5sen","orcid":null},"institutions":[{"id":"https://openalex.org/I163244428","display_name":"Norwegian Defence Research Establishment","ror":"https://ror.org/0098gnz32","country_code":"NO","type":"facility","lineage":["https://openalex.org/I163244428"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"I. Kasen","raw_affiliation_strings":["Norwegian Defence Research Establishment, Kjeller, Norway","Norwegian Defence Research Establishment (FFI) , Kjeller , Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian Defence Research Establishment, Kjeller, Norway","institution_ids":["https://openalex.org/I163244428"]},{"raw_affiliation_string":"Norwegian Defence Research Establishment (FFI) , Kjeller , Norway","institution_ids":["https://openalex.org/I163244428"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16243974,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"1","last_page":"4"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9754999876022339,"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"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9387999773025513,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/anomaly-detection","display_name":"Anomaly detection","score":0.8137487173080444},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7819322347640991},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.7791087031364441},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7622829079627991},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.690093994140625},{"id":"https://openalex.org/keywords/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.6321437358856201},{"id":"https://openalex.org/keywords/spectral-line","display_name":"Spectral line","score":0.5269730091094971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45757007598876953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45537954568862915},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.40387290716171265},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3898829221725464},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.16222703456878662},{"id":"https://openalex.org/keywords/astronomy","display_name":"Astronomy","score":0.06681153178215027}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8137487173080444},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7819322347640991},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7791087031364441},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7622829079627991},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.690093994140625},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.6321437358856201},{"id":"https://openalex.org/C4839761","wikidata":"https://www.wikidata.org/wiki/Q212111","display_name":"Spectral line","level":2,"score":0.5269730091094971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45757007598876953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45537954568862915},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.40387290716171265},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3898829221725464},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.16222703456878662},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.06681153178215027},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2011.6080971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2011.6080971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320318240","display_name":"European Space Agency","ror":"https://ror.org/03wd9za21"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1970099214","https://openalex.org/W1971180200","https://openalex.org/W2013211397","https://openalex.org/W2014238333","https://openalex.org/W2047870694","https://openalex.org/W2089607420","https://openalex.org/W2113340030","https://openalex.org/W2124267685","https://openalex.org/W2124463804","https://openalex.org/W6678426626"],"related_works":["https://openalex.org/W2076134148","https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969"],"abstract_inverted_index":{"Anomaly":[0,21],"detection":[1,22,103],"in":[2,25,74],"hyperspectral":[3,27],"data":[4,28],"has":[5],"received":[6],"much":[7],"attention":[8],"for":[9,16],"various":[10],"applications":[11],"and":[12,18,50,95,116,128],"is":[13,81],"especially":[14],"important":[15],"defense":[17],"security":[19],"applications.":[20],"detects":[23],"pixels":[24,55],"the":[26,35,42,45,62,82,87,91,96,101,111,117],"cube":[29],"whose":[30],"spectra":[31,43],"differ":[32],"significantly":[33],"from":[34],"background":[36,49,64],"spectra.":[37,65],"Most":[38],"existing":[39],"methods":[40],"estimate":[41],"of":[44,68,105,108,113,123],"(local":[46],"or":[47],"global)":[48],"then":[51],"detect":[52],"anomalies":[53],"as":[54],"with":[56],"a":[57],"large":[58],"spectral":[59],"distance":[60,89],"w.r.t.":[61],"determined":[63],"Many":[66],"types":[67],"anomaly":[69,79,109,119],"detectors":[70,115],"have":[71],"been":[72],"proposed":[73],"literature.":[75],"The":[76],"most":[77],"well-known":[78],"detector":[80,84],"RX":[83],"that":[85],"calculates":[86],"Mahalanobis":[88],"between":[90],"pixel":[92],"under":[93],"test":[94],"background.":[97],"This":[98],"paper":[99],"investigates":[100],"sub-pixel":[102],"performance":[104],"two":[106],"classes":[107],"detectors:":[110],"family":[112],"RX-based":[114],"segmentation-based":[118],"detectors.":[120],"Representative":[121],"examples":[122],"each":[124],"class":[125],"are":[126,135],"selected":[127],"results":[129],"obtained":[130],"on":[131],"three":[132],"different":[133],"datacubes":[134],"analyzed.":[136]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
