{"id":"https://openalex.org/W4384831931","doi":"https://doi.org/10.1109/msp.2023.3271438","title":"Superresolution Image Reconstruction: Selective milestones and open problems","display_name":"Superresolution Image Reconstruction: Selective milestones and open problems","publication_year":2023,"publication_date":"2023-07-01","ids":{"openalex":"https://openalex.org/W4384831931","doi":"https://doi.org/10.1109/msp.2023.3271438"},"language":"en","primary_location":{"id":"doi:10.1109/msp.2023.3271438","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/msp.2023.3271438","pdf_url":"https://ieeexplore.ieee.org/ielx7/79/10188464/10188481.pdf","source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/79/10188464/10188481.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100354039","display_name":"Xin Li","orcid":"https://orcid.org/0000-0003-2067-2763"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA","Sharp Laboratories of America, Camas, WA, USA"],"raw_orcid":"https://orcid.org/0000-0003-2067-2763","affiliations":[{"raw_affiliation_string":"Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, USA","institution_ids":["https://openalex.org/I12097938"]},{"raw_affiliation_string":"Sharp Laboratories of America, Camas, WA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037310802","display_name":"Weisheng Dong","orcid":"https://orcid.org/0000-0002-9632-985X"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]},{"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","HK"],"is_corresponding":false,"raw_author_name":"Weisheng Dong","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China","Department of Computing, Hong Kong Polytechnic University, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-9632-985X","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Department of Computing, Hong Kong Polytechnic University, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074780876","display_name":"Jinjian Wu","orcid":"https://orcid.org/0000-0001-7501-0009"},"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"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Jinjian Wu","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China","Nanyang Technological University, Singapore","Xidian University, China"],"raw_orcid":"https://orcid.org/0000-0001-7501-0009","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Xidian University, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033615240","display_name":"Leida Li","orcid":"https://orcid.org/0000-0001-9069-8796"},"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"]},{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Leida Li","raw_affiliation_strings":["School of Artificial Intelligence, Xidian University, Xi’an, China","School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-9069-8796","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101549504","display_name":"Guangming Shi","orcid":"https://orcid.org/0000-0003-2179-3292"},"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"]},{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK","US"],"is_corresponding":false,"raw_author_name":"Guangming Shi","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi’an, China","Department of Electronic Engineering, University of Hong Kong, Hong Kong","Department of Electronic Engineering, University of Illinois, Urbana Champaign, USA"],"raw_orcid":"https://orcid.org/0000-0003-2179-3292","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Department of Electronic Engineering, University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electronic Engineering, University of Illinois, Urbana Champaign, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8738,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.71396559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"40","issue":"5","first_page":"54","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9958999752998352,"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/T11897","display_name":"Digital Holography and Microscopy","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7535231113433838},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6912428140640259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6603050231933594},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5498993396759033},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.5090534090995789},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.49404123425483704},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48889604210853577},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4615822434425354},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.4607279300689697},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4249821901321411},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41703730821609497},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3298330008983612},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23824268579483032},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20671290159225464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7535231113433838},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6912428140640259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6603050231933594},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5498993396759033},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.5090534090995789},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.49404123425483704},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48889604210853577},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4615822434425354},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.4607279300689697},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4249821901321411},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41703730821609497},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3298330008983612},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23824268579483032},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20671290159225464},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/msp.2023.3271438","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/msp.2023.3271438","pdf_url":"https://ieeexplore.ieee.org/ielx7/79/10188464/10188481.pdf","source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/msp.2023.3271438","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1109/msp.2023.3271438","pdf_url":"https://ieeexplore.ieee.org/ielx7/79/10188464/10188481.pdf","source":{"id":"https://openalex.org/S120977877","display_name":"IEEE Signal Processing Magazine","issn_l":"1053-5888","issn":["1053-5888","1558-0792"],"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 Signal Processing Magazine","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4699999988079071}],"awards":[{"id":"https://openalex.org/G1586809628","display_name":null,"funder_award_id":"2018AAA0101400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G1725003993","display_name":null,"funder_award_id":"61621005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2706191583","display_name":null,"funder_award_id":"CMMI-2146015","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2817195743","display_name":null,"funder_award_id":"IIS-2114644","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4150153631","display_name":null,"funder_award_id":"61836008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4230951488","display_name":"HCC: Small: Toward Computational Modeling of Autism Spectrum Disorder: Multimodal Data Collection, Fusion, and Phenotyping","funder_award_id":"2114644","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6862244890","display_name":null,"funder_award_id":"61632019","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G712080188","display_name":null,"funder_award_id":"61991451","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384831931.pdf","grobid_xml":"https://content.openalex.org/works/W4384831931.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W935139217","https://openalex.org/W1885185971","https://openalex.org/W1976416062","https://openalex.org/W2067042811","https://openalex.org/W2097074225","https://openalex.org/W2117865218","https://openalex.org/W2121058967","https://openalex.org/W2124378283","https://openalex.org/W2140257560","https://openalex.org/W2163935418","https://openalex.org/W2165939075","https://openalex.org/W2172128189","https://openalex.org/W2214802144","https://openalex.org/W2503339013","https://openalex.org/W2534320940","https://openalex.org/W2607041014","https://openalex.org/W2747898905","https://openalex.org/W2866634454","https://openalex.org/W2891158090","https://openalex.org/W2954930822","https://openalex.org/W2963031226","https://openalex.org/W2963091558","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2963729050","https://openalex.org/W2964101377","https://openalex.org/W3013529009","https://openalex.org/W3034243376","https://openalex.org/W3034352949","https://openalex.org/W3036167779","https://openalex.org/W3040726448","https://openalex.org/W3085109118","https://openalex.org/W3155072588","https://openalex.org/W3174531399","https://openalex.org/W3180355996","https://openalex.org/W3180712890","https://openalex.org/W3193389639","https://openalex.org/W3193508667","https://openalex.org/W4223483730","https://openalex.org/W4306292690","https://openalex.org/W4312509301","https://openalex.org/W4312693498","https://openalex.org/W6753074096","https://openalex.org/W6779823529"],"related_works":["https://openalex.org/W2171218219","https://openalex.org/W1972271943","https://openalex.org/W2150410159","https://openalex.org/W2560215812","https://openalex.org/W3150905897","https://openalex.org/W2784452928","https://openalex.org/W3049172720","https://openalex.org/W1496347422","https://openalex.org/W2002670936","https://openalex.org/W2590412282"],"abstract_inverted_index":{"In":[0],"multidimensional":[1],"signal":[2],"processing,":[3,9],"such":[4,79],"as":[5,80],"image":[6],"and":[7,23,85,94,102,123,129,157,169,182],"video":[8],"superresolution":[10],"(SR)":[11],"imaging":[12],"is":[13],"a":[14,151,160],"classical":[15],"problem.":[16],"Over":[17],"the":[18,40,51,58,139,165],"past":[19],"25":[20],"years,":[21],"academia":[22],"industry":[24],"have":[25],"been":[26],"interested":[27],"in":[28,45,91],"reconstructing":[29],"high-resolution":[30],"(HR)":[31],"images":[32],"from":[33,64,138],"their":[34,136],"low-resolution":[35],"(LR)":[36],"counterparts.":[37],"We":[38,172],"review":[39],"development":[41],"of":[42,53,73,110,141,167],"SR":[43,74,98,106,131],"technology":[44],"this":[46],"tutorial":[47],"article":[48],"based":[49],"on":[50],"evolution":[52],"key":[54],"insights":[55],"associated":[56],"with":[57,75],"prior":[59],"knowledge":[60],"or":[61],"regularization":[62],"method":[63],"analytical":[65],"representations":[66],"to":[67,149],"data-driven":[68],"deep":[69,86],"models.":[70],"The":[71],"coevolution":[72],"other":[76],"technical":[77],"fields,":[78],"autoregressive":[81],"modeling,":[82],"sparse":[83],"coding,":[84],"learning,":[87],"will":[88,173],"be":[89],"highlighted":[90],"both":[92],"model-based":[93,128,168],"learning-based":[95,105,130,170],"approaches.":[96],"Model-based":[97],"includes":[99],"geometry-driven,":[100],"sparsity-based,":[101],"gradient-profile":[103],"priors;":[104],"covers":[107],"three":[108],"types":[109],"neural":[111],"network":[112],"(NN)":[113],"architectures,":[114],"namely":[115],"residual":[116],"networks":[117,121],"(ResNet),":[118],"generative":[119],"adversarial":[120],"(GANs),":[122],"pretrained":[124],"models":[125],"(PTMs).":[126],"Both":[127],"are":[132],"united":[133],"by":[134],"highlighting":[135],"limitations":[137],"perspective":[140,146],"model-data":[142],"mismatch.":[143],"Our":[144],"new":[145],"allows":[147],"us":[148],"maintain":[150],"healthy":[152],"skepticism":[153],"about":[154],"current":[155],"practice":[156],"advocate":[158],"for":[159],"hybrid":[161],"approach":[162],"that":[163],"combines":[164],"strengths":[166],"SR.":[171,184],"also":[174],"discuss":[175],"several":[176],"open":[177],"challenges,":[178],"including":[179],"arbitrary-ratio,":[180],"reference-based,":[181],"domain-specific":[183]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}