{"id":"https://openalex.org/W7124454587","doi":"https://doi.org/10.1109/tip.2025.3648872","title":"FourierSR: A Fourier Token-Based Plugin for Efficient Image Super-Resolution","display_name":"FourierSR: A Fourier Token-Based Plugin for Efficient Image Super-Resolution","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7124454587","doi":"https://doi.org/10.1109/tip.2025.3648872","pmid":"https://pubmed.ncbi.nlm.nih.gov/41538349"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2025.3648872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3648872","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","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/A5100408991","display_name":"Wenjie Li","orcid":"https://orcid.org/0000-0003-3086-5307"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Li","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3086-5307","affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123202103","display_name":"Heng Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Guo","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0047-3927","affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuefeng Hou","orcid":"https://orcid.org/0000-0003-4771-0619"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuefeng Hou","raw_affiliation_strings":["School of Microelectronics, Tianjin University (TJU), Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-4771-0619","affiliations":[{"raw_affiliation_string":"School of Microelectronics, Tianjin University (TJU), Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111245532","display_name":"Zhanyu Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanyu Ma","raw_affiliation_strings":["Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2950-2488","affiliations":[{"raw_affiliation_string":"Pattern Recognition and Intelligent System Laboratory, School of Artificial Intelligence, Beijing University of Posts and Telecommunications (BUPT), Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":39.5875,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.99672686,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"35","issue":null,"first_page":"732","last_page":"742"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9926999807357788,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9926999807357788,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.002300000051036477,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.0015999999595806003,"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/convolution","display_name":"Convolution (computer science)","score":0.6827999949455261},{"id":"https://openalex.org/keywords/flops","display_name":"FLOPS","score":0.6324999928474426},{"id":"https://openalex.org/keywords/plug-in","display_name":"Plug-in","score":0.5899999737739563},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5139999985694885},{"id":"https://openalex.org/keywords/discrete-fourier-transform","display_name":"Discrete Fourier transform (general)","score":0.48190000653266907},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4706000089645386},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.4499000012874603},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44609999656677246},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.4357999861240387},{"id":"https://openalex.org/keywords/security-token","display_name":"Security token","score":0.4325999915599823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7059000134468079},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6827999949455261},{"id":"https://openalex.org/C3826847","wikidata":"https://www.wikidata.org/wiki/Q188768","display_name":"FLOPS","level":2,"score":0.6324999928474426},{"id":"https://openalex.org/C4924752","wikidata":"https://www.wikidata.org/wiki/Q184148","display_name":"Plug-in","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5139999985694885},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.48190000653266907},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4706000089645386},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.4499000012874603},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44609999656677246},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44190001487731934},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.4357999861240387},{"id":"https://openalex.org/C48145219","wikidata":"https://www.wikidata.org/wiki/Q1335365","display_name":"Security token","level":2,"score":0.4325999915599823},{"id":"https://openalex.org/C75172450","wikidata":"https://www.wikidata.org/wiki/Q623950","display_name":"Fast Fourier transform","level":2,"score":0.428600013256073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4189000129699707},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.382099986076355},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.37540000677108765},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.37209999561309814},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.35089999437332153},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.34769999980926514},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.3472000062465668},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C146044194","wikidata":"https://www.wikidata.org/wiki/Q5157334","display_name":"Computational photography","level":4,"score":0.3084999918937683},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.2865999937057495},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28610000014305115},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C79587385","wikidata":"https://www.wikidata.org/wiki/Q2638931","display_name":"Convolution theorem","level":5,"score":0.27070000767707825},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C177066171","wikidata":"https://www.wikidata.org/wiki/Q284935","display_name":"Universal Plug and Play","level":2,"score":0.25929999351501465}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2025.3648872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2025.3648872","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:41538349","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41538349","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 image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.5251575708389282}],"awards":[{"id":"https://openalex.org/G172479822","display_name":null,"funder_award_id":"62225601","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1741159002","display_name":null,"funder_award_id":"62472044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6862892202","display_name":null,"funder_award_id":"U24B20155","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G807646956","display_name":null,"funder_award_id":"F2024502017","funder_id":"https://openalex.org/F4320328119","funder_display_name":"National University's Basic Research Foundation of China"},{"id":"https://openalex.org/G8677236040","display_name":null,"funder_award_id":"U23B2052","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"},{"id":"https://openalex.org/F4320328119","display_name":"National University's Basic Research Foundation of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1791560514","https://openalex.org/W1930824406","https://openalex.org/W2047920195","https://openalex.org/W2121927366","https://openalex.org/W2159269332","https://openalex.org/W2192954843","https://openalex.org/W2503339013","https://openalex.org/W2739757502","https://openalex.org/W2795024892","https://openalex.org/W2895598217","https://openalex.org/W2896927224","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963645458","https://openalex.org/W2976718572","https://openalex.org/W3010638262","https://openalex.org/W3012118477","https://openalex.org/W3049418625","https://openalex.org/W3133953507","https://openalex.org/W3138516171","https://openalex.org/W3162090017","https://openalex.org/W3170026688","https://openalex.org/W3176997885","https://openalex.org/W3207918547","https://openalex.org/W4221153217","https://openalex.org/W4225576932","https://openalex.org/W4226226289","https://openalex.org/W4287020683","https://openalex.org/W4292828883","https://openalex.org/W4312746248","https://openalex.org/W4312958254","https://openalex.org/W4367721896","https://openalex.org/W4378804909","https://openalex.org/W4386075509","https://openalex.org/W4386075642","https://openalex.org/W4386075678","https://openalex.org/W4386076602","https://openalex.org/W4387967967","https://openalex.org/W4390604941","https://openalex.org/W4390872521","https://openalex.org/W4390874458","https://openalex.org/W4393156599","https://openalex.org/W4394785970","https://openalex.org/W4402754029","https://openalex.org/W4402952320","https://openalex.org/W4402961660","https://openalex.org/W4403520967","https://openalex.org/W4403791406","https://openalex.org/W4403792190","https://openalex.org/W4403943510","https://openalex.org/W4404198585","https://openalex.org/W4405754140","https://openalex.org/W4409134989","https://openalex.org/W4413114136","https://openalex.org/W4413146328","https://openalex.org/W4413146346","https://openalex.org/W4416626030"],"related_works":[],"abstract_inverted_index":{"Image":[0],"super-resolution":[1],"(SR)":[2],"aims":[3],"to":[4,8,37,40,68,89],"recover":[5],"low-resolution":[6],"images":[7],"high-resolution":[9],"images,":[10],"where":[11],"improving":[12],"SR":[13,42,70,131],"efficiency":[14],"is":[15,155],"a":[16,62,118],"high-profile":[17],"challenge.":[18],"However,":[19],"commonly":[20],"used":[21],"units":[22],"in":[23,148],"SR,":[24],"like":[25],"convolutions":[26,90],"and":[27,91,100,153,158],"window-based":[28],"Transformers,":[29,93],"have":[30],"limited":[31,45],"receptive":[32,109],"fields,":[33],"making":[34],"it":[35],"challenging":[36],"apply":[38],"them":[39],"improve":[41,69],"under":[43],"extremely":[44],"computational":[46],"cost.":[47],"To":[48],"address":[49],"this":[50],"issue,":[51],"inspired":[52],"by":[53],"modeling":[54],"convolution":[55],"theorem":[56],"through":[57],"token":[58,80],"mix,":[59],"we":[60],"propose":[61],"Fourier":[63,98],"token-based":[64],"plugin":[65],"called":[66],"FourierSR":[67,95,116],"uniformly,":[71],"which":[72],"avoids":[73],"the":[74,138,145,149],"instability":[75],"or":[76],"inefficiency":[77],"of":[78,126,140,151,160],"existing":[79,129],"mix":[81],"technologies":[82],"when":[83],"applied":[84],"as":[85,117],"plug-ins.":[86],"Furthermore,":[87],"compared":[88],"windows-based":[92],"our":[94,115,166],"only":[96,156],"utilizes":[97],"transform":[99],"multiplication":[101],"operations,":[102],"greatly":[103],"reducing":[104],"complexity":[105],"while":[106,144],"having":[107],"global":[108],"fields.":[110],"Experimental":[111],"results":[112],"show":[113],"that":[114],"plug-and-play":[119],"unit":[120],"brings":[121],"an":[122],"average":[123,146],"PSNR":[124],"gain":[125],"0.34dB":[127],"for":[128],"efficient":[130],"methods":[132],"on":[133],"Manga109":[134],"test":[135],"set":[136],"at":[137],"scale":[139],"$\\times":[141],"4$":[142],",":[143],"increase":[147],"number":[150],"Params":[152],"FLOPs":[154],"0.6%":[157],"1.5%":[159],"original":[161],"sizes.":[162],"We":[163],"will":[164],"release":[165],"codes":[167],"upon":[168],"acceptance.":[169]},"counts_by_year":[{"year":2026,"cited_by_count":4}],"updated_date":"2026-01-26T23:06:41.788003","created_date":"2026-01-17T00:00:00"}
