{"id":"https://openalex.org/W4410583954","doi":"https://doi.org/10.1109/jstars.2025.3572252","title":"Generalized Likelihood Ratio Test for Hyperspectral Subpixel Target Detection Based on Segmented Mixing Model","display_name":"Generalized Likelihood Ratio Test for Hyperspectral Subpixel Target Detection Based on Segmented Mixing Model","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410583954","doi":"https://doi.org/10.1109/jstars.2025.3572252"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3572252","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3572252","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3572252","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yubo Ma","orcid":"https://orcid.org/0009-0002-3290-6811"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]},{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubo Ma","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, China","Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0002-3290-6811","affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"Research Institute of Electronic Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018461154","display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0002-6203-3583"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, China","College of Mathematics, Sichuan University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0000-0002-6203-3583","affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006769589","display_name":"Siyu Cai","orcid":"https://orcid.org/0009-0002-4811-9118"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyu Cai","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, China","College of Mathematics, Sichuan University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0002-4811-9118","affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":null,"display_name":"Qingke Zou","orcid":"https://orcid.org/0009-0009-3846-2992"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingke Zou","raw_affiliation_strings":["College of Mathematics, Sichuan University, Chengdu, China","College of Mathematics, Sichuan University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0009-3846-2992","affiliations":[{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]},{"raw_affiliation_string":"College of Mathematics, Sichuan University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":3.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91477527,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"18","issue":null,"first_page":"13678","last_page":"13690"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9570000171661377,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9570000171661377,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9531000256538391,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9488000273704529,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9265154600143433},{"id":"https://openalex.org/keywords/likelihood-ratio-test","display_name":"Likelihood-ratio test","score":0.6084838509559631},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5962628126144409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5374181270599365},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5101892948150635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49555861949920654},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.4588485658168793},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.419898122549057},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41967907547950745},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36815211176872253},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23181626200675964},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17531704902648926},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10826802253723145},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09938406944274902}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9265154600143433},{"id":"https://openalex.org/C9483764","wikidata":"https://www.wikidata.org/wiki/Q585740","display_name":"Likelihood-ratio test","level":2,"score":0.6084838509559631},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5962628126144409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5374181270599365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5101892948150635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49555861949920654},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.4588485658168793},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.419898122549057},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41967907547950745},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36815211176872253},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23181626200675964},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17531704902648926},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10826802253723145},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09938406944274902},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3572252","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3572252","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:105304738e194154a5d7885fae0174da","is_oa":true,"landing_page_url":"https://doaj.org/article/105304738e194154a5d7885fae0174da","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 13678-13690 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3572252","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3572252","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2572295718","display_name":null,"funder_award_id":"SCU2023D008","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":54,"referenced_works":["https://openalex.org/W1520754819","https://openalex.org/W1524571335","https://openalex.org/W1986921156","https://openalex.org/W2099301440","https://openalex.org/W2144158572","https://openalex.org/W2171521847","https://openalex.org/W2507498837","https://openalex.org/W2755992512","https://openalex.org/W2900574948","https://openalex.org/W2945634456","https://openalex.org/W2963129728","https://openalex.org/W2964064133","https://openalex.org/W2990385891","https://openalex.org/W2990709406","https://openalex.org/W3022984473","https://openalex.org/W3026092059","https://openalex.org/W3087883793","https://openalex.org/W3091247454","https://openalex.org/W3156696558","https://openalex.org/W3177111766","https://openalex.org/W4205690031","https://openalex.org/W4206550575","https://openalex.org/W4206590811","https://openalex.org/W4214751062","https://openalex.org/W4226239104","https://openalex.org/W4285235209","https://openalex.org/W4294982787","https://openalex.org/W4299591492","https://openalex.org/W4318586088","https://openalex.org/W4319759469","https://openalex.org/W4321486715","https://openalex.org/W4322576350","https://openalex.org/W4365443680","https://openalex.org/W4379230331","https://openalex.org/W4385602818","https://openalex.org/W4385627047","https://openalex.org/W4385945263","https://openalex.org/W4386025596","https://openalex.org/W4386858181","https://openalex.org/W4387803763","https://openalex.org/W4389161200","https://openalex.org/W4389474266","https://openalex.org/W4390097224","https://openalex.org/W4391594007","https://openalex.org/W4399243705","https://openalex.org/W4399401248","https://openalex.org/W4401358048","https://openalex.org/W4403445931","https://openalex.org/W4403827055","https://openalex.org/W4404293856","https://openalex.org/W4405718049","https://openalex.org/W4407737116","https://openalex.org/W4408100369","https://openalex.org/W4408145356"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W2800956885","https://openalex.org/W2076134148","https://openalex.org/W2533019003","https://openalex.org/W1788560349","https://openalex.org/W2626158795","https://openalex.org/W2078656815","https://openalex.org/W2391021239","https://openalex.org/W2560525382","https://openalex.org/W2126575155"],"abstract_inverted_index":{"For":[0,46],"hyperspectral":[1,166],"sub-pixel":[2,64],"target":[3,65,190],"detection":[4,66,172],"tasks,":[5],"conventional":[6],"mixing":[7,26,40,53,60,81,141],"model":[8,61],"(CMM)":[9],"is":[10,29,67,102,118,136,183],"one":[11],"of":[12,21,25,49,55,107,126,154],"the":[13,19,38,47,52,105,134,139,145,152,170,175,179],"most":[14],"intensively":[15],"used":[16],"models.":[17],"Despite":[18],"flexibility":[20],"CMM":[22],"in":[23,185],"terms":[24],"coefficient,":[27,82],"it":[28],"sometimes":[30],"inappropriate":[31],"to":[32,119,137,187],"assume":[33],"that":[34,78,169],"all":[35],"bands":[36,74],"share":[37],"same":[39,80],"coefficient":[41],"for":[42,63,123],"high-dimensional":[43],"spectral":[44,73],"vectors.":[45],"sake":[48],"finely":[50],"characterizing":[51],"structure":[54],"different":[56],"endmembers,":[57],"a":[58,76,94,121],"segmented":[59,140],"(SMM)":[62],"constructed.":[68],"In":[69],"this":[70],"model,":[71],"adjacent":[72],"form":[75],"segment":[77],"shares":[79],"and":[83,133,143,164,178],"segments":[84],"are":[85],"separated":[86],"from":[87],"each":[88],"other":[89,135],"under":[90,104,151],"some":[91,188],"optimality.":[92],"Then,":[93],"segmented-mixing-based":[95],"generalized":[96,146],"likelihood":[97,147],"ratio":[98,148],"test":[99,149],"(SMGLRT)":[100],"detector":[101,182],"developed":[103],"framework":[106],"statistical":[108],"hypothesis":[109],"testing,":[110],"which":[111],"concentrates":[112],"on":[113,129,162],"solving":[114],"two":[115],"problems.":[116],"One":[117],"create":[120],"criterion":[122],"evaluating":[124],"performance":[125],"segmentation":[127],"based":[128],"block-diagonal":[130],"covariance":[131],"matrix,":[132],"estimate":[138],"coefficients":[142],"derive":[144],"statistic":[150],"assumption":[153],"background":[155],"pixels":[156],"obeying":[157],"Gaussian":[158],"mixture":[159],"distribution.":[160],"Experiments":[161],"real":[163],"synthetic":[165],"images":[167],"show":[168],"SMM-based":[171],"outperforms":[173],"than":[174],"CMM-based":[176],"one,":[177],"proposed":[180],"SMGLRT":[181],"superior":[184],"contrast":[186],"classical":[189],"detectors.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
