{"id":"https://openalex.org/W7124868735","doi":"https://doi.org/10.1109/access.2026.3655362","title":"Multi-Scale Factor Super-Resolution for Light Field Images","display_name":"Multi-Scale Factor Super-Resolution for Light Field Images","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124868735","doi":"https://doi.org/10.1109/access.2026.3655362"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3655362","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655362","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3655362","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076368122","display_name":"Xiyao Hua","orcid":null},"institutions":[{"id":"https://openalex.org/I4401041622","display_name":"Chengdu Technological University","ror":"https://ror.org/04713ex73","country_code":null,"type":"education","lineage":["https://openalex.org/I4401041622"]},{"id":"https://openalex.org/I44468530","display_name":"Qingdao University of Technology","ror":"https://ror.org/01qzc0f54","country_code":"CN","type":"education","lineage":["https://openalex.org/I44468530"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiyao Hua","raw_affiliation_strings":["School of Big Data and Artificial Intelligence, Chengdu Technological University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0008-3966-1363","affiliations":[{"raw_affiliation_string":"School of Big Data and Artificial Intelligence, Chengdu Technological University, Chengdu, China","institution_ids":["https://openalex.org/I4401041622","https://openalex.org/I44468530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100845389","display_name":"Boni Su","orcid":null},"institutions":[{"id":"https://openalex.org/I4401041622","display_name":"Chengdu Technological University","ror":"https://ror.org/04713ex73","country_code":null,"type":"education","lineage":["https://openalex.org/I4401041622"]},{"id":"https://openalex.org/I44468530","display_name":"Qingdao University of Technology","ror":"https://ror.org/01qzc0f54","country_code":"CN","type":"education","lineage":["https://openalex.org/I44468530"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boni Su","raw_affiliation_strings":["School of Big Data and Artificial Intelligence, Chengdu Technological University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0000-3666-6830","affiliations":[{"raw_affiliation_string":"School of Big Data and Artificial Intelligence, Chengdu Technological University, Chengdu, China","institution_ids":["https://openalex.org/I4401041622","https://openalex.org/I44468530"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06779389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"12900","last_page":"12916"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9099000096321106,"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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9099000096321106,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.03700000047683716,"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/T10540","display_name":"Advanced Fluorescence Microscopy Techniques","score":0.005400000140070915,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.9301999807357788},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6776999831199646},{"id":"https://openalex.org/keywords/light-field","display_name":"Light field","score":0.5555999875068665},{"id":"https://openalex.org/keywords/scale-factor","display_name":"Scale factor (cosmology)","score":0.536300003528595},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.5360999703407288},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5271000266075134},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5077999830245972},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4880000054836273}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9301999807357788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7394999861717224},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6776999831199646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6766999959945679},{"id":"https://openalex.org/C48983235","wikidata":"https://www.wikidata.org/wiki/Q593161","display_name":"Light field","level":2,"score":0.5555999875068665},{"id":"https://openalex.org/C144386022","wikidata":"https://www.wikidata.org/wiki/Q1332997","display_name":"Scale factor (cosmology)","level":5,"score":0.536300003528595},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.5360999703407288},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5271000266075134},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5242999792098999},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5077999830245972},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4880000054836273},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4832000136375427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.41620001196861267},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3474000096321106},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33079999685287476},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29750001430511475},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3655362","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655362","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3655362","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3655362","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W2042687553","https://openalex.org/W2105198794","https://openalex.org/W2239879258","https://openalex.org/W2242218935","https://openalex.org/W2289524987","https://openalex.org/W2320359495","https://openalex.org/W2476548250","https://openalex.org/W2503339013","https://openalex.org/W2551052086","https://openalex.org/W2572840108","https://openalex.org/W2588196171","https://openalex.org/W2591697814","https://openalex.org/W2607041014","https://openalex.org/W2744570394","https://openalex.org/W2783178946","https://openalex.org/W2892310177","https://openalex.org/W2895527865","https://openalex.org/W2903622424","https://openalex.org/W2914600502","https://openalex.org/W2947690922","https://openalex.org/W2963031226","https://openalex.org/W2963372104","https://openalex.org/W2998715827","https://openalex.org/W3003377035","https://openalex.org/W3035271082","https://openalex.org/W3038678488","https://openalex.org/W3103166891","https://openalex.org/W3110151525","https://openalex.org/W3185226086","https://openalex.org/W3186548293","https://openalex.org/W3202903235","https://openalex.org/W3207991954","https://openalex.org/W3210054798","https://openalex.org/W4213117431","https://openalex.org/W4312709602","https://openalex.org/W4360897648","https://openalex.org/W4379116850","https://openalex.org/W4390872220","https://openalex.org/W4393372246","https://openalex.org/W4405179021","https://openalex.org/W4414404778","https://openalex.org/W4414499292"],"related_works":[],"abstract_inverted_index":{"Light":[0],"field":[1,84],"image":[2],"super-resolution":[3],"(LFSR)":[4],"has":[5],"achieved":[6],"significant":[7],"progress":[8],"with":[9],"the":[10,29,82,98,106,118],"rapid":[11],"development":[12],"of":[13,33,79],"deep":[14],"learning":[15],"techniques.":[16],"However,":[17],"most":[18],"existing":[19],"methods":[20,150],"are":[21],"limited":[22],"to":[23,108,148],"a":[24,58,73,153],"single":[25,74,154],"scale":[26,115,159],"factor,":[27],"requiring":[28],"training":[30],"and":[31,44,92,95,117,137],"storage":[32],"separate":[34],"models":[35],"for":[36,51,113,128,156],"each":[37],"upsampling":[38,121],"task":[39],"(e.g.,":[40],"2\u00d7/4\u00d7":[41],"spatial":[42,94],"SR":[43],"7\u00d77/8\u00d78":[45],"angular":[46,96],"SR),":[47],"which":[48,65,89,104,124],"is":[49],"inefficient":[50],"deployment.":[52],"In":[53],"this":[54],"paper,":[55],"we":[56],"propose":[57],"unified":[59],"end-to-end":[60],"framework,":[61],"termed":[62],"as":[63],"MLFSR,":[64],"can":[66],"handle":[67],"multi-scale":[68,119],"factor":[69,120],"LFSR":[70],"tasks":[71],"within":[72],"model.":[75],"The":[76],"MLFR":[77],"consists":[78],"three":[80],"modules:":[81],"light":[83],"feature":[85,100,111],"disentangling":[86],"module":[87,102,122],"(LFDM),":[88],"effectively":[90],"separates":[91],"fuses":[93],"features;":[97],"scale-aware":[99],"adaptation":[101],"(SFAM),":[103],"enables":[105],"network":[107],"adaptively":[109],"process":[110],"representations":[112],"different":[114],"factors;":[116],"(MFUM),":[123],"utilizes":[125],"task-specific":[126],"sub-modules":[127],"efficient":[129],"high-resolution":[130],"reconstruction.":[131],"Extensive":[132],"experiments":[133],"on":[134],"both":[135],"synthetic":[136],"real-world":[138],"datasets":[139],"demonstrate":[140],"that":[141],"our":[142],"method":[143],"achieves":[144],"competitive":[145],"performance":[146],"compared":[147],"state-of-the-art":[149],"while":[151],"maintaining":[152],"model":[155],"all":[157],"tested":[158],"factors.":[160]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-01-21T00:00:00"}
