{"id":"https://openalex.org/W4400077048","doi":"https://doi.org/10.1109/tetci.2024.3414950","title":"Global Cross-Attention Network for Single-Sensor Multispectral Imaging","display_name":"Global Cross-Attention Network for Single-Sensor Multispectral Imaging","publication_year":2024,"publication_date":"2024-06-27","ids":{"openalex":"https://openalex.org/W4400077048","doi":"https://doi.org/10.1109/tetci.2024.3414950"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2024.3414950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2024.3414950","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","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/A5018762110","display_name":"Nianzeng Yuan","orcid":"https://orcid.org/0009-0004-7183-7294"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nianzeng Yuan","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x0027;an University of Technology, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0009-0004-7183-7294","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x0027;an University of Technology, Xi&#x0027;an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046113804","display_name":"Junhuai Li","orcid":"https://orcid.org/0000-0001-5483-5175"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junhuai Li","raw_affiliation_strings":["School of Computer Science and Engineering, Xi&#x0027;an University of Technology, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0000-0001-5483-5175","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi&#x0027;an University of Technology, Xi&#x0027;an, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070913913","display_name":"Bangyong Sun","orcid":"https://orcid.org/0000-0002-0265-1785"},"institutions":[{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bangyong Sun","raw_affiliation_strings":["School of Printing, Packaging and Digital Media, Xi&#x0027;an University of Technology, Xi&#x0027;an, China"],"raw_orcid":"https://orcid.org/0000-0002-0265-1785","affiliations":[{"raw_affiliation_string":"School of Printing, Packaging and Digital Media, Xi&#x0027;an University of Technology, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I4210131919"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7965,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93427962,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"9","issue":"1","first_page":"240","last_page":"252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9275000095367432,"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"}},"topics":[{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9275000095367432,"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/multispectral-image","display_name":"Multispectral image","score":0.894206702709198},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4921552538871765},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4745037257671356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3685048818588257},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3498387336730957},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2340443730354309}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.894206702709198},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4921552538871765},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4745037257671356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3685048818588257},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3498387336730957},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2340443730354309}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2024.3414950","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2024.3414950","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4350466949","display_name":null,"funder_award_id":"62076199","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1965061537","https://openalex.org/W1971072214","https://openalex.org/W1977970101","https://openalex.org/W1980372154","https://openalex.org/W2010319424","https://openalex.org/W2022007237","https://openalex.org/W2023009596","https://openalex.org/W2032491448","https://openalex.org/W2032603438","https://openalex.org/W2043960878","https://openalex.org/W2058127401","https://openalex.org/W2066203729","https://openalex.org/W2075686424","https://openalex.org/W2082136663","https://openalex.org/W2091500847","https://openalex.org/W2100109944","https://openalex.org/W2104940379","https://openalex.org/W2107557661","https://openalex.org/W2118550318","https://openalex.org/W2133665775","https://openalex.org/W2146795245","https://openalex.org/W2150445969","https://openalex.org/W2295904998","https://openalex.org/W2410797836","https://openalex.org/W2462824656","https://openalex.org/W2557236696","https://openalex.org/W2604425999","https://openalex.org/W2773272881","https://openalex.org/W2807301514","https://openalex.org/W2811424548","https://openalex.org/W2884188838","https://openalex.org/W2913724932","https://openalex.org/W2936172565","https://openalex.org/W2993025393","https://openalex.org/W3003353074","https://openalex.org/W3012359476","https://openalex.org/W3024465739","https://openalex.org/W3033535123","https://openalex.org/W3124773035","https://openalex.org/W3127661997","https://openalex.org/W3132115664","https://openalex.org/W3185385692","https://openalex.org/W3193497103","https://openalex.org/W3196922068","https://openalex.org/W3197841412","https://openalex.org/W3201461236","https://openalex.org/W3207918547","https://openalex.org/W4205130528","https://openalex.org/W4224294196","https://openalex.org/W4225672218","https://openalex.org/W4285300354","https://openalex.org/W4289536378","https://openalex.org/W4292794036","https://openalex.org/W4312349930","https://openalex.org/W4321484009","https://openalex.org/W4362683589","https://openalex.org/W4362690177","https://openalex.org/W4385245566","https://openalex.org/W6602248423","https://openalex.org/W6754090299","https://openalex.org/W6755977528","https://openalex.org/W6757788932","https://openalex.org/W6757817989","https://openalex.org/W6768429979","https://openalex.org/W7046007472"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Multispectral":[0],"filter":[1],"array":[2],"(MSFA)":[3],"imaging":[4,26],"with":[5,31,44,129],"one":[6],"single":[7],"sensor":[8],"is":[9,27,67,83,105,137,170],"a":[10,60,92,96,101],"fast,":[11],"portable,":[12],"and":[13,95,117,123,145,166,190,198,214],"inexpensive":[14],"means":[15],"of":[16,34,53,81,143,212],"acquiring":[17],"spectral":[18,72,118,125,168,215],"images.":[19],"The":[20,79],"most":[21],"challenging":[22],"task":[23],"for":[24,41,147],"MSFA":[25],"the":[28,32,36,42,50,54,76,86,133,141,155,167,203],"multispectral":[29,77],"demosaicing":[30,65],"aim":[33],"reconstructing":[35],"captured":[37],"raw/mosaic":[38],"image,":[39],"especially":[40],"systems":[43],"many":[45],"bands":[46],"which":[47,90],"results":[48],"in":[49,113,210],"higher":[51],"sparseness":[52],"raw":[55],"data.":[56],"In":[57,183],"this":[58],"paper,":[59],"global":[61,87,102,124],"cross-attention":[62,88,103],"network":[63],"(GCN)":[64],"method":[66,177],"proposed":[68,106,175,204],"to":[69,74,107,139,163,179],"excavate":[70],"latent":[71],"characteristics":[73,112],"reconstruct":[75],"image.":[78],"architecture":[80],"GCN":[82,176,185,205],"based":[84],"on":[85],"module,":[89],"contains":[91],"cross-transformer":[93],"layer":[94],"local":[97,134,148],"self-attention":[98,122,126,135],"module.":[99],"Specifically,":[100],"module":[104,136],"fully":[108],"explore":[109],"intrinsic":[110],"similarity":[111,169],"both":[114,196],"spatial":[115,121,149,213],"dimension":[116],"dimension,":[119],"non-local":[120],"are":[127],"conducted":[128],"Transformer":[130],"architecture.":[131],"Besides,":[132],"utilized":[138],"enhance":[140],"effectiveness":[142],"extraction":[144],"refinement":[146],"information.":[150],"Simulation":[151],"experiments":[152],"show":[153],"that":[154,202],"image":[156],"quality":[157],"can":[158],"be":[159],"improved":[160,172],"by":[161,173],"up":[162],"1.78":[164],"dB":[165],"significantly":[171,186],"our":[174],"compared":[178],"various":[180],"reconstruction":[181],"methods.":[182],"addition,":[184],"reduces":[187],"false":[188],"color":[189],"zipper":[191],"effect":[192],"artifacts.":[193],"Experiments":[194],"using":[195],"synthetic":[197],"real":[199],"data":[200],"demonstrate":[201],"outperforms":[206],"state-of-the-art":[207],"(SOTA)":[208],"methods":[209],"terms":[211],"fidelity.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
