{"id":"https://openalex.org/W4312572145","doi":"https://doi.org/10.1109/tgrs.2022.3211786","title":"Comprehensive Analysis of Receiver Operating Characteristic (ROC) Curves for Hyperspectral Anomaly Detection","display_name":"Comprehensive Analysis of Receiver Operating Characteristic (ROC) Curves for Hyperspectral Anomaly Detection","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312572145","doi":"https://doi.org/10.1109/tgrs.2022.3211786"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3211786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3211786","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/A5073412670","display_name":"Chein\u2010I Chang","orcid":"https://orcid.org/0000-0002-5450-4891"},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]},{"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"]}],"countries":["CN","US"],"is_corresponding":true,"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","Department of Computer Science and Electrical Engineering, Remote Sensing Signal and Image Processing Laboratory, University of Maryland, 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":"Department of Computer Science and Electrical Engineering, Remote Sensing Signal and Image Processing Laboratory, University of Maryland, Baltimore, MD, USA","institution_ids":["https://openalex.org/I126744593"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5073412670"],"corresponding_institution_ids":["https://openalex.org/I126744593","https://openalex.org/I43313876"],"apc_list":null,"apc_paid":null,"fwci":4.609,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.95517386,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"24"},"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":0.9714000225067139,"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":0.968999981880188,"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/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.9100278615951538},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5256040096282959},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5146540403366089},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5039655566215515},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4879886507987976},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.46940886974334717},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.4309900403022766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42755988240242004},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3571386933326721},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3405790328979492},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33480140566825867},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1604606807231903}],"concepts":[{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.9100278615951538},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5256040096282959},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5146540403366089},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5039655566215515},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4879886507987976},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.46940886974334717},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.4309900403022766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42755988240242004},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3571386933326721},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3405790328979492},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33480140566825867},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1604606807231903},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3211786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3211786","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":46,"referenced_works":["https://openalex.org/W1968525434","https://openalex.org/W1968631366","https://openalex.org/W1972578813","https://openalex.org/W2017331394","https://openalex.org/W2043052030","https://openalex.org/W2047870694","https://openalex.org/W2067782748","https://openalex.org/W2068970203","https://openalex.org/W2115927538","https://openalex.org/W2121101670","https://openalex.org/W2142552707","https://openalex.org/W2144158572","https://openalex.org/W2154236340","https://openalex.org/W2295576075","https://openalex.org/W2493273699","https://openalex.org/W2549107715","https://openalex.org/W2590856740","https://openalex.org/W2613586935","https://openalex.org/W2789806937","https://openalex.org/W2795739134","https://openalex.org/W2899937451","https://openalex.org/W2901773810","https://openalex.org/W2911876518","https://openalex.org/W2938260698","https://openalex.org/W2949079224","https://openalex.org/W2969635036","https://openalex.org/W3003955104","https://openalex.org/W3005109735","https://openalex.org/W3008839601","https://openalex.org/W3021090805","https://openalex.org/W3080792885","https://openalex.org/W3087883793","https://openalex.org/W3093449804","https://openalex.org/W3107126660","https://openalex.org/W3112037842","https://openalex.org/W3119966815","https://openalex.org/W3133603318","https://openalex.org/W3137199127","https://openalex.org/W3156696558","https://openalex.org/W3177111766","https://openalex.org/W3195212285","https://openalex.org/W3199351457","https://openalex.org/W3210780861","https://openalex.org/W4220831207","https://openalex.org/W4248253651","https://openalex.org/W4312289230"],"related_works":["https://openalex.org/W2072006507","https://openalex.org/W4232993046","https://openalex.org/W2085485627","https://openalex.org/W2076520961","https://openalex.org/W2003125512","https://openalex.org/W2385759983","https://openalex.org/W3133467894","https://openalex.org/W2245446703","https://openalex.org/W2365251477","https://openalex.org/W2045444723"],"abstract_inverted_index":{"The":[0],"receiver":[1],"operating":[2],"characteristic":[3],"(ROC)":[4],"curve":[5,45,72,82,104,123,195],"of":[6,41,120,199,215,224,254],"detection":[7,30],"probability":[8,14,75],"(PD)":[9],"versus":[10],"the":[11,57,85],"false":[12],"alarm":[13],"(PF),":[15],"referred":[16],"to":[17,26,107,170,246,267],"as":[18,87,95,196],"2D":[19,43,80,121,221,273],"ROC":[20,44,71,81,103,122,194,218,222,274],"curve,":[21,219],"has":[22,50],"been":[23,51],"widely":[24],"used":[25,46,106],"evaluate":[27,108],"hyperspectral":[28],"anomaly":[29,255,263],"(AD)":[31],"performance.":[32],"This":[33,175],"article":[34],"explores":[35],"several":[36],"fundamental":[37],"and":[38,53,91,148,150,211,234,257],"conceptual":[39],"issues":[40],"a":[42,61,79,88,96,117,127,133,163,188,192,197,216],"for":[47,66,190],"AD,":[48],"which":[49,144],"overlooked":[52],"never":[54],"investigated":[55],"in":[56,84,252,281],"past.":[58],"How":[59,68,100],"can":[60,101,243],"Neyman\u2013Pearson":[62,129],"(NP)":[63],"detector":[64,130],"work":[65],"AD?":[67],"is":[69,78,124,168],"an":[70,102],"plotted":[73],"without":[74],"distributions?":[76],"Why":[77],"reported":[83],"literature":[86],"step":[89],"function":[90,198],"later":[92],"linearly":[93],"interpolated":[94],"linear":[97],"piecewise":[98],"function?":[99],"be":[105,244],"background":[109],"suppression":[110],"(BS)?":[111],"To":[112],"address":[113],"all":[114],"these":[115],"issues,":[116],"mathematical":[118],"theory":[119],"rederived":[125],"by":[126],"random":[128],"(RNPD)":[131],"via":[132],"threshold":[134,176],"parameter":[135],"<inline-formula":[136,177,202,227,236],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[137,178,203,228,237],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[138,179,204,229,238],"<tex-math":[139,180,205,230,239],"notation=\"LaTeX\">$\\tau":[140,181,206],"$":[141,182,207],"</tex-math></inline-formula>":[142,183,208,232,241],",":[143,209],"actually":[145,277],"determines":[146],"PD":[147],"PF,":[149],"its":[151],"detailed":[152],"theoretical":[153],"proofs":[154],"along":[155],"with":[156],"comprehensive":[157],"analysis":[158,250],"are":[159,276],"also":[160],"provided.":[161],"Specifically,":[162],"binary":[164],"communication":[165],"channel":[166],"example":[167],"included":[169],"illustrate":[171],"how":[172],"RNPD":[173],"works.":[174],"-driven":[184],"approach,":[185],"indeed,":[186],"paves":[187],"way":[189],"deriving":[191],"3D":[193,217],"three":[200,220],"parameters:":[201],"PD,":[210],"PF.":[212],"By":[213],"virtue":[214],"curves":[223,275],"(PD,PF),":[225],"(PD,":[226],"notation=\"LaTeX\">$\\tau$":[231,240],"),":[233],"(PF,":[235],")":[242],"derived":[245],"perform":[247,268],"AD":[248,271],"performance":[249],"effectively":[251],"terms":[253],"detectability":[256],"BS.":[258,282],"Experiments":[259],"demonstrate":[260],"that":[261,265],"many":[262],"detectors":[264],"claim":[266],"well":[269],"on":[270],"using":[272],"performed":[278],"very":[279],"poorly":[280]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}