{"id":"https://openalex.org/W2984604230","doi":"https://doi.org/10.23919/eusipco.2019.8902338","title":"Multiple-Degradation Video Super-Resolution with Direct Inversion of the Low-Resolution Formation Model","display_name":"Multiple-Degradation Video Super-Resolution with Direct Inversion of the Low-Resolution Formation Model","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2984604230","doi":"https://doi.org/10.23919/eusipco.2019.8902338","mag":"2984604230"},"language":"en","primary_location":{"id":"doi:10.23919/eusipco.2019.8902338","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5046773255","display_name":"Santiago L\u00f3pez-Tapia","orcid":"https://orcid.org/0000-0003-2090-7446"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Santiago Lopez-Tapia","raw_affiliation_strings":["Depto. de Ciencias de la Computaci\u00f3n e I.A., University of Granada, Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Depto. de Ciencias de la Computaci\u00f3n e I.A., University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043771227","display_name":"Alice Lucas","orcid":"https://orcid.org/0000-0001-5914-4154"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alice Lucas","raw_affiliation_strings":["Dept. of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023830568","display_name":"Rafael Molina","orcid":"https://orcid.org/0000-0003-4694-8588"},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Rafael Molina","raw_affiliation_strings":["Depto. de Ciencias de la Computaci\u00f3n e I.A., University of Granada, Granada, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Depto. de Ciencias de la Computaci\u00f3n e I.A., University of Granada, Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048650003","display_name":"Aggelos K. Katsaggelos","orcid":"https://orcid.org/0000-0003-4554-0070"},"institutions":[{"id":"https://openalex.org/I111979921","display_name":"Northwestern University","ror":"https://ror.org/000e0be47","country_code":"US","type":"education","lineage":["https://openalex.org/I111979921"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aggelos K. Katsaggelos","raw_affiliation_strings":["Dept. of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA","institution_ids":["https://openalex.org/I111979921"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0915,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.37677352,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.998199999332428,"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":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.9083654880523682},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7779287099838257},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.7329009175300598},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6455193758010864},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.6114644408226013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48765289783477783},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4773269295692444},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4623843729496002},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.43692517280578613},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.42633140087127686},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35777896642684937},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3259866237640381},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.29370924830436707},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.14287430047988892},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09766751527786255}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9083654880523682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7779287099838257},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.7329009175300598},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6455193758010864},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.6114644408226013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48765289783477783},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4773269295692444},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4623843729496002},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.43692517280578613},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.42633140087127686},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35777896642684937},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3259866237640381},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29370924830436707},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.14287430047988892},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09766751527786255},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/eusipco.2019.8902338","is_oa":false,"landing_page_url":"https://doi.org/10.23919/eusipco.2019.8902338","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 27th European Signal Processing Conference (EUSIPCO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1999666556","https://openalex.org/W2010981316","https://openalex.org/W2103346247","https://openalex.org/W2103824707","https://openalex.org/W2138598313","https://openalex.org/W2167191464","https://openalex.org/W2170820036","https://openalex.org/W2200125188","https://openalex.org/W2210480155","https://openalex.org/W2320725294","https://openalex.org/W2476548250","https://openalex.org/W2537458122","https://openalex.org/W2557227117","https://openalex.org/W2589026418","https://openalex.org/W2613155248","https://openalex.org/W2726582817","https://openalex.org/W2781335552","https://openalex.org/W2808109260","https://openalex.org/W2950560720","https://openalex.org/W2964040059","https://openalex.org/W2964121744","https://openalex.org/W2964277374","https://openalex.org/W3101569186","https://openalex.org/W4211167357","https://openalex.org/W6631190155","https://openalex.org/W6730015810","https://openalex.org/W6733850229"],"related_works":["https://openalex.org/W3202223591","https://openalex.org/W3216158842","https://openalex.org/W4288103895","https://openalex.org/W3012322483","https://openalex.org/W3203374800","https://openalex.org/W2974792966","https://openalex.org/W2914107945","https://openalex.org/W2801811999","https://openalex.org/W4291801625","https://openalex.org/W2963241118"],"abstract_inverted_index":{"With":[0],"the":[1,12,16,84,92,108],"increase":[2],"of":[3,5,18,91,107],"popularity":[4],"high":[6,9],"and":[7,51,82],"ultra":[8],"definition":[10],"displays,":[11],"need":[13],"to":[14,47,78],"improve":[15],"quality":[17],"content":[19],"already":[20],"obtained":[21],"at":[22],"much":[23],"lower":[24],"resolutions":[25],"has":[26],"grown.":[27],"Since":[28],"current":[29,105],"video":[30,72],"super-resolution":[31],"methods":[32],"are":[33,44],"trained":[34],"with":[35],"a":[36,66],"single":[37],"degradation":[38,53,80],"model":[39,88],"(usually":[40],"bicubic":[41],"downsampling),":[42],"they":[43],"not":[45],"robust":[46,77],"mismatch":[48],"between":[49],"training":[50],"testing":[52],"models,":[54],"in":[55],"which":[56,75],"case":[57],"their":[58],"performance":[59],"deteriorates.":[60],"In":[61],"this":[62],"work":[63],"we":[64],"propose":[65],"new":[67],"Convolutional":[68],"Neural":[69],"Network":[70],"for":[71],"super":[73],"resolution":[74],"is":[76],"multiple":[79],"models":[81],"uses":[83],"pseudo-inverse":[85],"image":[86],"formation":[87],"as":[89],"part":[90],"network":[93],"architecture":[94],"during":[95],"training.":[96],"The":[97],"experimental":[98],"validation":[99],"shows":[100],"that":[101],"our":[102],"approach":[103],"outperforms":[104],"state":[106],"art":[109],"methods.":[110]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}