{"id":"https://openalex.org/W4312817981","doi":"https://doi.org/10.1109/tim.2022.3216403","title":"Adaptive Infrared and Visible Image Fusion Based on Visual Saliency and Hierarchical Bayesian","display_name":"Adaptive Infrared and Visible Image Fusion Based on Visual Saliency and Hierarchical Bayesian","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312817981","doi":"https://doi.org/10.1109/tim.2022.3216403"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3216403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3216403","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5025887750","display_name":"Sunsi Fu","orcid":"https://orcid.org/0000-0003-0293-0722"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sunsi Fu","raw_affiliation_strings":["School of Information Science and Engineering, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0293-0722","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012950180","display_name":"Rushan Zheng","orcid":"https://orcid.org/0000-0003-0839-1774"},"institutions":[{"id":"https://openalex.org/I4210086892","display_name":"Education University of Hong Kong","ror":"https://ror.org/000t0f062","country_code":"HK","type":"education","lineage":["https://openalex.org/I4210086892"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Rushan Zheng","raw_affiliation_strings":["Department of Mathematics and Information Technology, The Education University of Hong Kong, Pokfulam, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-0839-1774","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Information Technology, The Education University of Hong Kong, Pokfulam, Hong Kong","institution_ids":["https://openalex.org/I4210086892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049673705","display_name":"Xiong Chen","orcid":"https://orcid.org/0000-0001-5476-4047"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Chen","raw_affiliation_strings":["School of Information Science and Engineering, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5476-4047","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7912,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7558431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9980999827384949,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9968000054359436,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6743137836456299},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6592639684677124},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6022653579711914},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.575934886932373},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5264502167701721},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5011489391326904},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.45496684312820435},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4504830837249756},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4161166548728943},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3658515214920044},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.07139775156974792}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6743137836456299},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6592639684677124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6022653579711914},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.575934886932373},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5264502167701721},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5011489391326904},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.45496684312820435},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4504830837249756},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4161166548728943},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3658515214920044},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.07139775156974792},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3216403","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3216403","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1563899710","https://openalex.org/W1708141795","https://openalex.org/W1965301399","https://openalex.org/W1980382026","https://openalex.org/W1997596006","https://openalex.org/W2021345820","https://openalex.org/W2028781966","https://openalex.org/W2049633694","https://openalex.org/W2054273865","https://openalex.org/W2059193044","https://openalex.org/W2062599688","https://openalex.org/W2065533005","https://openalex.org/W2088856702","https://openalex.org/W2103504761","https://openalex.org/W2113199232","https://openalex.org/W2116702374","https://openalex.org/W2125232112","https://openalex.org/W2133665775","https://openalex.org/W2146353910","https://openalex.org/W2182501874","https://openalex.org/W2196001564","https://openalex.org/W2216437871","https://openalex.org/W2256359941","https://openalex.org/W2266694576","https://openalex.org/W2346484933","https://openalex.org/W2522212509","https://openalex.org/W2576508765","https://openalex.org/W2589745805","https://openalex.org/W2610070095","https://openalex.org/W2613594293","https://openalex.org/W2798483734","https://openalex.org/W2806456004","https://openalex.org/W2896171544","https://openalex.org/W2900598697","https://openalex.org/W2912147220","https://openalex.org/W3024215945","https://openalex.org/W3039415429","https://openalex.org/W3043904761","https://openalex.org/W3083923056","https://openalex.org/W3102411220","https://openalex.org/W3108042295","https://openalex.org/W3126994406","https://openalex.org/W3129015415","https://openalex.org/W3147076409","https://openalex.org/W4292363360","https://openalex.org/W6649524578","https://openalex.org/W6750688579","https://openalex.org/W7048738093"],"related_works":["https://openalex.org/W3124942695","https://openalex.org/W1750358731","https://openalex.org/W2788731446","https://openalex.org/W2139242969","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2370195708","https://openalex.org/W1490651872"],"abstract_inverted_index":{"An":[0],"adaptive":[1,93],"infrared":[2],"and":[3,12,24,52,67,125,143,146,161,174],"visible":[4],"image":[5,47,148],"fusion":[6,94,112,129,158,167],"method":[7],"based":[8,114],"on":[9,115,140],"visual":[10,117],"saliency":[11,118],"hierarchical":[13,127],"Bayesian":[14,128],"(AVSHB)":[15],"which":[16,98],"preserves":[17],"the":[18,79,81,101,122,134,141,178],"highest":[19],"similarity":[20],"between":[21],"fused":[22],"images":[23,26],"source":[25,46,179],"is":[27,41,64,96,131],"proposed":[28,97],"in":[29,75],"this":[30],"paper.":[31],"Firstly,":[32],"an":[33,92],"effective":[34],"salient":[35,84,172],"edge":[36],"preserving":[37],"filter":[38],"named":[39],"SEPF":[40],"developed":[42],"to":[43],"decompose":[44],"each":[45,104],"into":[48,70],"a":[49,53,71,110,116,126],"base":[50,123],"layer":[51],"detail":[54,135],"layer.":[55,105],"A":[56],"\u2113":[57],"<sub":[58],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[59],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[60],"norm":[61],"gradient":[62],"minimization":[63],"firstly":[65],"derived":[66,132],"then":[68],"embedded":[69],"two-scale":[72,111],"acceleration":[73],"scheme":[74,95],"SEPF.":[76],"Benefiting":[77],"from":[78,177],"SEPF,":[80],"edges":[82],"of":[83,103],"regions":[85],"can":[86,164],"be":[87],"preserved":[88],"without":[89],"distortion.":[90],"Then,":[91],"fully":[99],"considers":[100],"characteristics":[102],"More":[106],"concretely,":[107],"we":[108],"design":[109],"strategy":[113],"map":[119],"(VSM)":[120],"for":[121,133],"layers,":[124],"model":[130],"layers.":[136],"The":[137],"experimental":[138],"results":[139,168],"TNO":[142],"RoadScene":[144],"datasets":[145],"Nato_camp":[147],"sequence":[149],"demonstrate":[150],"that":[151],"AVSHB":[152,163],"favorably":[153],"outperforms":[154],"16":[155],"related":[156],"state-of-the-art":[157],"methods":[159],"qualitatively":[160],"quantitatively.":[162],"generate":[165],"improved":[166],"with":[169],"sufficiently":[170],"retaining":[171],"targets":[173],"rich":[175],"details":[176],"images.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
