{"id":"https://openalex.org/W4210365123","doi":"https://doi.org/10.1109/tnnls.2022.3142780","title":"Deep Selective Fusion of Visible and Near-Infrared Images Using Unsupervised U-Net","display_name":"Deep Selective Fusion of Visible and Near-Infrared Images Using Unsupervised U-Net","publication_year":2022,"publication_date":"2022-01-31","ids":{"openalex":"https://openalex.org/W4210365123","doi":"https://doi.org/10.1109/tnnls.2022.3142780","pmid":"https://pubmed.ncbi.nlm.nih.gov/35100123"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3142780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3142780","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5009504456","display_name":"Qihui Han","orcid":"https://orcid.org/0000-0002-6506-1563"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qihui Han","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xian, China","School of Electronic Engineering, Xidian University, Xian 710071, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian 710071, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003623628","display_name":"Cheolkon Jung","orcid":"https://orcid.org/0000-0003-0299-7206"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheolkon Jung","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xian, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xian, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009504456"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":null,"apc_paid":null,"fwci":1.7608,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.85652235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"36","issue":"3","first_page":"4172","last_page":"4183"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9979000091552734,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9969000220298767,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8420596122741699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.674248456954956},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6348541975021362},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6070823073387146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5891885161399841},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5524967908859253},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5217664837837219},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5053718686103821},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.46667349338531494},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45703116059303284},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4257952570915222},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41029125452041626},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23654744029045105}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8420596122741699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.674248456954956},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6348541975021362},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6070823073387146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5891885161399841},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5524967908859253},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5217664837837219},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5053718686103821},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.46667349338531494},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45703116059303284},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4257952570915222},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41029125452041626},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23654744029045105},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3142780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3142780","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35100123","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35100123","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G2237013747","display_name":null,"funder_award_id":"61872280","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4457358854","display_name":null,"funder_award_id":"62111540272","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":51,"referenced_works":["https://openalex.org/W1563899710","https://openalex.org/W1901129140","https://openalex.org/W1964641132","https://openalex.org/W1972398042","https://openalex.org/W1983874169","https://openalex.org/W1990873664","https://openalex.org/W2012893378","https://openalex.org/W2014711337","https://openalex.org/W2058749767","https://openalex.org/W2083388902","https://openalex.org/W2091484864","https://openalex.org/W2091649119","https://openalex.org/W2095295506","https://openalex.org/W2102166818","https://openalex.org/W2125188192","https://openalex.org/W2126074213","https://openalex.org/W2129211628","https://openalex.org/W2133665775","https://openalex.org/W2136001449","https://openalex.org/W2142060261","https://openalex.org/W2164517370","https://openalex.org/W2168078737","https://openalex.org/W2306859282","https://openalex.org/W2575511118","https://openalex.org/W2590560192","https://openalex.org/W2600975391","https://openalex.org/W2724862036","https://openalex.org/W2798018774","https://openalex.org/W2798987894","https://openalex.org/W2809795042","https://openalex.org/W2902225124","https://openalex.org/W2912147220","https://openalex.org/W2963134949","https://openalex.org/W2963530785","https://openalex.org/W2971146307","https://openalex.org/W2991399532","https://openalex.org/W2998816125","https://openalex.org/W3002696208","https://openalex.org/W3007891240","https://openalex.org/W3043904761","https://openalex.org/W3046194589","https://openalex.org/W3092444386","https://openalex.org/W3102515681","https://openalex.org/W3102946988","https://openalex.org/W3105639468","https://openalex.org/W3108042295","https://openalex.org/W3129015415","https://openalex.org/W3158080681","https://openalex.org/W6637373629","https://openalex.org/W6752788502","https://openalex.org/W6762854505"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272","https://openalex.org/W1989561795"],"abstract_inverted_index":{"In":[0,58],"low":[1,10,83],"light":[2],"conditions,":[3],"visible":[4],"(VIS)":[5],"images":[6,23,37,40,71,87,141,154,159],"are":[7,79],"of":[8,33,41,53,67,104,112,233],"a":[9,126,161,199],"dynamic":[11],"range":[12],"(low":[13],"contrast)":[14],"with":[15,81,131,216],"severe":[16],"noise":[17,28,48],"and":[18,29,35,46,55,69,88,142,155,195,221,224,236],"color,":[19],"while":[20],"near-infrared":[21],"(NIR)":[22],"contain":[24],"clear":[25],"textures":[26],"without":[27],"color.":[30],"Multispectral":[31],"fusion":[32,66,77,103,210],"VIS":[34,54,68,86,153,175],"NIR":[36,56,70,92,158,188],"produces":[38,212],"color":[39,223],"high":[42],"quality,":[43],"rich":[44],"textures,":[45],"little":[47,219],"by":[49,120,139,150],"taking":[50],"both":[51],"advantages":[52],"images.":[57,93,176,189],"this":[59],"article,":[60],"we":[61,95,116,135,164,178,191],"propose":[62],"the":[63,82,110,113,208],"deep":[64,101],"selective":[65,102],"using":[72,160],"unsupervised":[73,97,118],"U-Net.":[74],"Existing":[75],"image":[76],"methods":[78,230],"afflicted":[80],"contrast":[84],"in":[85,91,231],"flash-like":[89],"effect":[90],"Thus,":[94],"adopt":[96],"U-Net":[98],"to":[99,109,171,183,228],"achieve":[100],"multiple":[105],"scale":[106],"features.":[107],"Due":[108],"absence":[111],"ground":[114],"truth,":[115],"use":[117],"learning":[119],"formulating":[121],"an":[122,180],"energy":[123],"function":[124],"as":[125],"loss":[127],"function.":[128],"To":[129],"deal":[130],"insufficient":[132],"training":[133,148],"data,":[134],"perform":[136],"data":[137,149],"augmentation":[138],"rotating":[140],"adjusting":[143],"their":[144],"intensity.":[145],"We":[146],"synthesize":[147],"degrading":[151],"clean":[152,157],"masking":[156],"circle.":[162],"First,":[163],"utilize":[165],"pretrained":[166],"visual":[167,234],"geometry":[168],"group":[169],"(VGG)":[170],"extract":[172],"features":[173,194],"from":[174,187],"Second,":[177],"build":[179],"encoding":[181],"network":[182,201,211],"obtain":[184],"edge":[185],"information":[186],"Finally,":[190],"combine":[192],"all":[193],"feed":[196],"them":[197],"into":[198],"decoding":[200],"for":[202],"fusion.":[203],"Experimental":[204],"results":[205,215],"demonstrate":[206],"that":[207],"proposed":[209],"visually":[213],"pleasing":[214],"fine":[217],"details,":[218],"noise,":[220],"natural":[222],"it":[225],"is":[226],"superior":[227],"state-of-the-art":[229],"terms":[232],"quality":[235],"quantitative":[237],"measurements.":[238]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}