{"id":"https://openalex.org/W3156696558","doi":"https://doi.org/10.1109/tgrs.2021.3069716","title":"Hyperspectral Target Detection: Hypothesis Testing, Signal-to-Noise Ratio, and Spectral Angle Theories","display_name":"Hyperspectral Target Detection: Hypothesis Testing, Signal-to-Noise Ratio, and Spectral Angle Theories","publication_year":2021,"publication_date":"2021-04-12","ids":{"openalex":"https://openalex.org/W3156696558","doi":"https://doi.org/10.1109/tgrs.2021.3069716","mag":"3156696558"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3069716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3069716","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":8.9695,"has_fulltext":false,"cited_by_count":94,"citation_normalized_percentile":{"value":0.98188119,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"23"},"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"}}],"keywords":[{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.6248793601989746},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5125100612640381},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4391652047634125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39302414655685425},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3898162245750427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3717104196548462},{"id":"https://openalex.org/keywords/philosophy","display_name":"Philosophy","score":0.08346119523048401},{"id":"https://openalex.org/keywords/arithmetic","display_name":"Arithmetic","score":0.06582382321357727}],"concepts":[{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.6248793601989746},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5125100612640381},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4391652047634125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39302414655685425},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3898162245750427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3717104196548462},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.08346119523048401},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.06582382321357727},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3069716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3069716","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":[{"id":"https://openalex.org/G1447177257","display_name":null,"funder_award_id":"3132019341","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1580026167","https://openalex.org/W1899348529","https://openalex.org/W1972578813","https://openalex.org/W1973176871","https://openalex.org/W2047870694","https://openalex.org/W2067782748","https://openalex.org/W2076008153","https://openalex.org/W2090862158","https://openalex.org/W2095665557","https://openalex.org/W2096972831","https://openalex.org/W2097900616","https://openalex.org/W2107820823","https://openalex.org/W2110211064","https://openalex.org/W2115366158","https://openalex.org/W2116939452","https://openalex.org/W2117741752","https://openalex.org/W2118996198","https://openalex.org/W2144158572","https://openalex.org/W2150347412","https://openalex.org/W2154236340","https://openalex.org/W2163436471","https://openalex.org/W2163957348","https://openalex.org/W2164535280","https://openalex.org/W2428361224","https://openalex.org/W2493273699","https://openalex.org/W2790801839","https://openalex.org/W2899937451","https://openalex.org/W2948763898","https://openalex.org/W3035042772","https://openalex.org/W3087883793","https://openalex.org/W3129037655","https://openalex.org/W3133603318","https://openalex.org/W3195212285","https://openalex.org/W4205778870","https://openalex.org/W4248253651","https://openalex.org/W6677508755"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W1979597421","https://openalex.org/W2007980826","https://openalex.org/W2051487156","https://openalex.org/W2504004674","https://openalex.org/W2061531152","https://openalex.org/W3002753104","https://openalex.org/W2077600819","https://openalex.org/W2142036596","https://openalex.org/W2072657027"],"abstract_inverted_index":{"Hyperspectral":[0],"target":[1,27,39,54,76,81,91,104,110,123,133],"detection":[2,40,82,92,111,146,152,162,178,225,231,243],"(HTD)":[3],"can":[4,83,214],"be":[5,12,64,84,202],"generally":[6],"categorized":[7],"by":[8],"its":[9],"targets":[10,23,51],"to":[11,63,94,113,142,170,183,228,255],"detected,":[13],"<inline-formula":[14,30,42,67,95,114],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[15,21,31,37,43,49,68,74,96,102,115,121],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">":[16,32,44,69,97,116],"<tex-math":[17,33,45,70,98,117],"notation=\"LaTeX\">$a$":[18,34,46,71,99,118],"</tex-math></inline-formula>":[19,35,47,72,100,119],"<italic":[20,36,48,73,101,120],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">priori</i>":[22,38,103],"with":[24,52],"provided":[25],"known":[26,53],"knowledge":[28],"as":[29,66,167,195],"and":[41,106,108,174,222,260],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">posteriori</i>":[50,75,122],"signatures":[55],"(spectral":[56],"shapes),":[57],"but":[58],"unknown":[59],"abundance":[60],"fractions":[61],"needed":[62],"estimated":[65],"detection.":[77,124],"As":[78],"a":[79,168,257],"result,":[80],"performed":[85],"in":[86,218],"three":[87,130,138,239],"scenarios,":[88],"full":[89],"pure-pixel":[90],"corresponding":[93,112],"detection,":[105,134],"subpixel":[107],"mixed-pixel":[109],"To":[125],"develop":[126],"theories":[127],"for":[128],"these":[129,238],"types":[131],"of":[132,187],"this":[135],"article":[136],"develops":[137],"approaches.":[139],"One":[140],"is":[141],"rederive":[143],"hypothesis":[144,196,207],"testing-based":[145],"theory":[147,163,179,221],"using":[148],"very":[149],"basic":[150],"statistical":[151],"theory.":[153,226],"Another":[154],"two":[155],"are":[156,253],"new":[157],"theories,":[158],"signal-to-noise":[159],"ratio":[160,210],"(SNR)-based":[161],"that":[164,180,204],"uses":[165],"SNR":[166],"criterion":[169],"derive":[171],"optimal":[172],"detectors":[173,213,235],"spectral":[175],"angle":[176],"(SA)-based":[177],"calculates":[181],"SA":[182],"perform":[184],"HTD,":[185],"both":[186],"which":[188],"do":[189],"not":[190],"require":[191],"prior":[192],"probability":[193],"distributions":[194],"testing":[197],"does.":[198],"Specifically,":[199],"it":[200],"will":[201],"shown":[203],"many":[205],"current":[206],"testing-derived":[208],"likelihood":[209],"test":[211],"(LRT)-based":[212],"find":[215],"their":[216],"counterparts":[217],"the":[219,223,230,234],"SNR-derived":[220],"SA-derived":[224],"Finally,":[227],"evaluate":[229],"performance":[232],"among":[233],"developed":[236],"from":[237,246],"approaches,":[240],"several":[241],"effective":[242],"measures":[244],"resulting":[245],"3-D":[247],"receiver":[248],"operating":[249],"characteristic":[250],"(ROC)":[251],"analysis":[252],"used":[254],"conduct":[256],"comprehensive":[258],"study":[259],"comparative":[261],"analysis.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":19},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}