{"id":"https://openalex.org/W3007098358","doi":"https://doi.org/10.1109/tgrs.2019.2961703","title":"Subpixel-Pixel-Superpixel Guided Fusion for Hyperspectral Anomaly Detection","display_name":"Subpixel-Pixel-Superpixel Guided Fusion for Hyperspectral Anomaly Detection","publication_year":2020,"publication_date":"2020-02-28","ids":{"openalex":"https://openalex.org/W3007098358","doi":"https://doi.org/10.1109/tgrs.2019.2961703","mag":"3007098358"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2019.2961703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2961703","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/A5063874284","display_name":"Zhihong Huang","orcid":"https://orcid.org/0000-0003-0549-1059"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihong Huang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-0549-1059","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065061505","display_name":"Leyuan Fang","orcid":"https://orcid.org/0000-0003-2351-4461"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyuan Fang","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-2351-4461","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067097659","display_name":"Shutao Li","orcid":"https://orcid.org/0000-0002-0585-9848"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shutao Li","raw_affiliation_strings":["College of Electrical and Information Engineering, Hunan University, Changsha, China","Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0002-0585-9848","affiliations":[{"raw_affiliation_string":"College of Electrical and Information Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]},{"raw_affiliation_string":"Key Laboratory of Visual Perception and Artificial Intelligence of Hunan Province, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":4.3489,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.94938133,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"58","issue":"9","first_page":"5998","last_page":"6007"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.970300018787384,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.968999981880188,"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/subpixel-rendering","display_name":"Subpixel rendering","score":0.9668007493019104},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9093738794326782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7389742136001587},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6967546343803406},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6703442335128784},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.626155436038971},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6068283915519714},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5456843376159668},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.44566643238067627},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.42910903692245483},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41804203391075134},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41536426544189453}],"concepts":[{"id":"https://openalex.org/C68516990","wikidata":"https://www.wikidata.org/wiki/Q452912","display_name":"Subpixel rendering","level":3,"score":0.9668007493019104},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9093738794326782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7389742136001587},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6967546343803406},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6703442335128784},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.626155436038971},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6068283915519714},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5456843376159668},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.44566643238067627},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.42910903692245483},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41804203391075134},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41536426544189453}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2019.2961703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2961703","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":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G898426514","display_name":null,"funder_award_id":"61520106001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1939429412","https://openalex.org/W1970099214","https://openalex.org/W1972023071","https://openalex.org/W1975610128","https://openalex.org/W1991190032","https://openalex.org/W2004104348","https://openalex.org/W2004491663","https://openalex.org/W2010702969","https://openalex.org/W2020210211","https://openalex.org/W2037034832","https://openalex.org/W2039039627","https://openalex.org/W2040078680","https://openalex.org/W2043441451","https://openalex.org/W2047519171","https://openalex.org/W2047870694","https://openalex.org/W2049444988","https://openalex.org/W2059063187","https://openalex.org/W2072187267","https://openalex.org/W2085529604","https://openalex.org/W2095343758","https://openalex.org/W2111560151","https://openalex.org/W2116702374","https://openalex.org/W2118996198","https://openalex.org/W2124267685","https://openalex.org/W2124463804","https://openalex.org/W2125298866","https://openalex.org/W2133059825","https://openalex.org/W2135431554","https://openalex.org/W2139987077","https://openalex.org/W2141195754","https://openalex.org/W2141957843","https://openalex.org/W2145858287","https://openalex.org/W2145962650","https://openalex.org/W2157321686","https://openalex.org/W2158340226","https://openalex.org/W2160956336","https://openalex.org/W2163129097","https://openalex.org/W2219019129","https://openalex.org/W2288752886","https://openalex.org/W2295576075","https://openalex.org/W2296385512","https://openalex.org/W2343117455","https://openalex.org/W2424277038","https://openalex.org/W2592141703","https://openalex.org/W2613575128","https://openalex.org/W2626256547","https://openalex.org/W2740976805","https://openalex.org/W2754507318","https://openalex.org/W2802773275","https://openalex.org/W2884073548","https://openalex.org/W2900199428","https://openalex.org/W2911876518","https://openalex.org/W2955002903","https://openalex.org/W2998514558","https://openalex.org/W4285719527","https://openalex.org/W6677508755"],"related_works":["https://openalex.org/W2369528593","https://openalex.org/W2385629811","https://openalex.org/W2111510641","https://openalex.org/W2638735979","https://openalex.org/W2386795888","https://openalex.org/W1968995436","https://openalex.org/W2382389562","https://openalex.org/W2054875742","https://openalex.org/W3088486721","https://openalex.org/W2884029982"],"abstract_inverted_index":{"Most":[0],"of":[1,83,115,127,146],"the":[2,67,80,112,128,144,147],"existing":[3],"hyperspectral":[4,24,45],"anomaly":[5,46],"detectors":[6,16],"are":[7,60],"designed":[8],"based":[9,78],"on":[10,79,133],"a":[11,37,86,101,121],"single":[12],"pixel-level":[13],"feature.":[14],"These":[15],"may":[17],"not":[18],"adequately":[19],"utilize":[20,111],"spectral-spatial":[21],"information":[22,114],"in":[23],"images":[25],"(HSIs)":[26],"for":[27,44,98],"detecting":[28],"anomalies.":[29],"To":[30],"overcome":[31],"this":[32,34],"problem,":[33],"article":[35],"introduces":[36],"novel":[38],"subpixel-pixel-superpixel":[39],"guided":[40,87],"fusion":[41,106],"(SPSGF)":[42],"method":[43,107],"detection.":[47],"This":[48],"approach":[49,130],"comprises":[50],"three":[51,84,116,134],"main":[52],"steps.":[53],"First,":[54],"subpixel-,":[55],"pixel-,":[56],"and":[57,72,118,137],"superpixel-level":[58],"features":[59],"extracted":[61],"from":[62],"an":[63],"HSI":[64],"by":[65],"employing":[66],"spectral":[68],"unmixing,":[69],"morphological":[70],"operation,":[71],"superpixel":[73],"segmentation":[74],"techniques,":[75],"respectively.":[76],"Then,":[77],"spatial":[81],"consistency":[82],"features,":[85,117],"filtering-based":[88],"weight":[89,96],"optimization":[90],"technique":[91],"is":[92,108,131],"developed":[93],"to":[94,110],"construct":[95],"maps":[97],"fusion.":[99],"Finally,":[100],"simple":[102],"yet":[103],"effective":[104],"decision":[105],"adopted":[109],"complemental":[113],"then":[119],"generates":[120],"fused":[122],"detection":[123],"result.":[124],"The":[125],"performance":[126],"proposed":[129],"evaluated":[132],"real-scene":[135],"HSIs":[136],"one":[138],"synthetic":[139],"HSI.":[140],"Experimental":[141],"results":[142],"validate":[143],"advantages":[145],"SPSGF":[148],"method.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
