{"id":"https://openalex.org/W3206961616","doi":"https://doi.org/10.1145/3480651.3480656","title":"Infrared and visible image fusion method based on LatLRR and ICA","display_name":"Infrared and visible image fusion method based on LatLRR and ICA","publication_year":2021,"publication_date":"2021-07-28","ids":{"openalex":"https://openalex.org/W3206961616","doi":"https://doi.org/10.1145/3480651.3480656","mag":"3206961616"},"language":"en","primary_location":{"id":"doi:10.1145/3480651.3480656","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3480651.3480656","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 3rd International Conference on Pattern Recognition and Intelligent Systems","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/A5019557372","display_name":"Ying Huang","orcid":"https://orcid.org/0000-0002-3840-951X"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Huang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104038437","display_name":"Zongyu Zhang","orcid":"https://orcid.org/0009-0004-8548-3845"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongyu Zhang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078656664","display_name":"Xilin Wen","orcid":"https://orcid.org/0009-0006-9589-3324"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xilin Wen","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1265,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5066722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2019","issue":null,"first_page":"20","last_page":"23"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9965999722480774,"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":0.9950000047683716,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7970409393310547},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.7064127922058105},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6618646383285522},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.653593897819519},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6273393630981445},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6074452996253967},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.5811835527420044},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5320727825164795},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.49124211072921753},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4802244305610657},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47885677218437195},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4130019545555115},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.40301376581192017},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24475768208503723}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7970409393310547},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.7064127922058105},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6618646383285522},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.653593897819519},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6273393630981445},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6074452996253967},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.5811835527420044},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5320727825164795},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.49124211072921753},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4802244305610657},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47885677218437195},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4130019545555115},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.40301376581192017},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24475768208503723},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3480651.3480656","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3480651.3480656","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 3rd International Conference on Pattern Recognition and Intelligent Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1964641132","https://openalex.org/W1997596006","https://openalex.org/W2054273865","https://openalex.org/W2091484864","https://openalex.org/W2099741732","https://openalex.org/W2133665775","https://openalex.org/W2153777140","https://openalex.org/W2310105885","https://openalex.org/W2912147220","https://openalex.org/W4241307704"],"related_works":["https://openalex.org/W2121429698","https://openalex.org/W2182042810","https://openalex.org/W4252230435","https://openalex.org/W55679925","https://openalex.org/W3080404860","https://openalex.org/W2046761971","https://openalex.org/W3144722888","https://openalex.org/W2364896863","https://openalex.org/W2586688824","https://openalex.org/W126272167"],"abstract_inverted_index":{"To":[0],"solve":[1],"the":[2,11,38,58,69,77,86,100,107,110,114,122,136],"problem":[3],"of":[4,7,20,61,88,117],"missing":[5],"lots":[6],"texture":[8],"details":[9],"in":[10,34],"fusion":[12,18,130],"image,":[13],"we":[14],"propose":[15],"a":[16,97],"new":[17],"method":[19,138],"infrared":[21,62],"and":[22,30,48,64,92,113,143],"visible":[23,65],"images":[24,91],"based":[25],"on":[26],"latent":[27],"low-rank":[28,44,59,111],"representation(LatLRR)":[29],"independent":[31],"component":[32],"analysis(ICA)":[33],"this":[35],"paper.":[36],"Firstly,":[37],"source":[39,74,90],"image":[40,63,66,78,102,119],"is":[41,55,82,94,103],"decomposed":[42],"into":[43],"components,":[45,47,112],"sparse":[46,115],"noise":[49],"components":[50,116],"by":[51,84,105,125],"LatLRR.":[52],"Secondly,":[53],"ICA":[54],"utilized":[56],"for":[57],"part":[60],"to":[67,121],"obtain":[68],"main":[70],"difference":[71],"between":[72],"two":[73,89],"images.":[75],"Then,":[76],"containing":[79],"more":[80],"information":[81],"determined":[83],"comparing":[85],"entropy":[87],"it":[93],"employed":[95],"as":[96],"benchmark.":[98],"Finally,":[99],"fused":[101],"accomplished":[104],"connecting":[106],"benchmark":[108],"result,":[109],"another":[118],"according":[120],"result":[123],"obtained":[124],"ICA.":[126],"Compared":[127],"with":[128],"other":[129],"methods,":[131],"experimental":[132],"results":[133],"demonstrate":[134],"that":[135],"proposed":[137],"has":[139],"better":[140],"visual":[141],"effects":[142],"evaluation":[144],"indicators.":[145]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}