{"id":"https://openalex.org/W4285340838","doi":"https://doi.org/10.1145/3513142.3513196","title":"Visible and infrared Image Fusion via Convolution Analysis Operator","display_name":"Visible and infrared Image Fusion via Convolution Analysis Operator","publication_year":2021,"publication_date":"2021-10-29","ids":{"openalex":"https://openalex.org/W4285340838","doi":"https://doi.org/10.1145/3513142.3513196"},"language":"en","primary_location":{"id":"doi:10.1145/3513142.3513196","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3513142.3513196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 4th International Conference on Information Technologies and Electrical Engineering","raw_type":"proceedings-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/A5101577714","display_name":"Chengfang Zhang","orcid":null},"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"]},{"id":"https://openalex.org/I4210145669","display_name":"Shanghai Police College","ror":"https://ror.org/0479fds27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210145669"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengfang Zhang","raw_affiliation_strings":["National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, China and Center of Laboratory and Equipment, Sichuan police college, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, China and Center of Laboratory and Equipment, Sichuan police college, China","institution_ids":["https://openalex.org/I4210145669","https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031943397","display_name":"Ziliang Feng","orcid":"https://orcid.org/0000-0001-6484-7612"},"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":"Ziliang Feng","raw_affiliation_strings":["National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32437527,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9962000250816345,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9904999732971191,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6986839175224304},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6133473515510559},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.5758016109466553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5436339974403381},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5435507297515869},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.529319703578949},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5017306804656982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4911348521709442},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3847252130508423},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.21954727172851562},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.189014732837677},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.07306131720542908}],"concepts":[{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6986839175224304},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6133473515510559},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.5758016109466553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5436339974403381},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5435507297515869},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.529319703578949},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5017306804656982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4911348521709442},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3847252130508423},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.21954727172851562},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.189014732837677},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.07306131720542908},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3513142.3513196","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3513142.3513196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 4th International Conference on Information Technologies and Electrical Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1563899710","https://openalex.org/W1628236353","https://openalex.org/W1946953458","https://openalex.org/W1969299043","https://openalex.org/W2091484864","https://openalex.org/W2142060261","https://openalex.org/W2146353910","https://openalex.org/W2165174801","https://openalex.org/W2179019672","https://openalex.org/W2190662802","https://openalex.org/W2266694576","https://openalex.org/W2293078015","https://openalex.org/W2532801510","https://openalex.org/W2546974981","https://openalex.org/W2589745805","https://openalex.org/W2610070095","https://openalex.org/W2772136803","https://openalex.org/W2798018774","https://openalex.org/W2798483734","https://openalex.org/W2912147220","https://openalex.org/W2918001912","https://openalex.org/W2952071070","https://openalex.org/W2971503239","https://openalex.org/W2989848928","https://openalex.org/W2990486577","https://openalex.org/W2997542096","https://openalex.org/W3016744618","https://openalex.org/W3066646572","https://openalex.org/W3112107364","https://openalex.org/W3112774412","https://openalex.org/W3121751387","https://openalex.org/W3213777593","https://openalex.org/W4250316874","https://openalex.org/W6673124941","https://openalex.org/W6684385272"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2549658594","https://openalex.org/W2095903272","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331"],"abstract_inverted_index":{"As":[0],"a":[1,96],"synthetic":[2],"model,":[3],"conventional":[4],"convolutional":[5,53,105],"sparse":[6],"representation":[7],"(CSR)/convolutional":[8],"dictionary":[9],"learning":[10,56],"(CDL)":[11],"suffers":[12],"from":[13],"model":[14,49,74],"mismatch.":[15],"This":[16],"deficiency":[17],"leads":[18],"to":[19,71,91,118,124],"loss":[20],"of":[21,35,43,81,132,174,212],"details":[22],"and":[23,50,94,112,136,144,151,178,189,215],"smoothing":[24],"in":[25,127,168,210],"infrared-visible":[26,98],"fusion":[27,83,93,100],"results":[28,201],"with":[29,69,162],"CDL/CSR":[30],"methods.":[31],"Based":[32],"on":[33,103,138],"study":[34],"analytic":[36,54],"operator":[37,55],"learning,":[38,164],"Chun":[39],"introduces":[40,87],"the":[41,52,61,73,79,88,104,147,156,165,172,185,194,204,208],"idea":[42,90],"convolution":[44],"into":[45],"an":[46],"\u201danalytic\u201d":[47],"signal":[48],"proposes":[51,95],"(CAOL)":[57],"framework.":[58],"CAOL":[59,89],"uses":[60],"convergent":[62],"block":[63],"proximal":[64],"extrapolation":[65],"gradient":[66],"method":[67,101,206],"(BPEG-M)":[68],"majorizer":[70],"solve":[72],"mismatch":[75],"problem.":[76],"To":[77],"avoid":[78],"shortcomings":[80],"CDL/CSR-based":[82],"methods,":[84],"this":[85,169],"paper":[86,170],"image":[92,99,122],"new":[97],"based":[102],"operation":[106],"analysis":[107],"operator.":[108],"The":[109,129,199],"proposed":[110,166,205],"framework":[111,167],"11":[113],"representative":[114],"methods":[115],"are":[116,141],"applied":[117],"8":[119,139],"common":[120],"infrared/visible":[121],"sets":[123],"verify":[125],"performance":[126,173],"experiments.":[128],"average":[130],"values":[131],"metrics":[133,175],"QABF,":[134],"QE,":[135],"QP":[137],"examples":[140],"0.6071,":[142],"0.4011,":[143],"0.4137":[145],"(for":[146,155,184,193],"\u201dcity\u201d":[148],"training":[149,158,187,196],"set)":[150,188],"0.6065,":[152],"0.4036,":[153],"0.4131":[154],"\u201dfruit\u201d":[157],"set),":[159,197],"respectively.":[160,198],"Compared":[161],"deep":[163],"improves":[171],"(QABF,":[176],"QE":[177],"QP)":[179],"by":[180],"15.13%,":[181],"22.79%,":[182],"13.37%":[183],"\u2019city\u2019":[186],"15.02%,":[190],"23.37%,":[191],"13.25%":[192],"\u2019fruit\u2019":[195],"experimental":[200],"show":[202],"that":[203],"surpasses":[207],"state-of-the-art":[209],"terms":[211],"visual":[213],"quality":[214],"objective":[216],"assessment.":[217]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
