{"id":"https://openalex.org/W2998785217","doi":"https://doi.org/10.1109/tci.2020.2964202","title":"Efficient and Interpretable Deep Blind Image Deblurring Via Algorithm Unrolling","display_name":"Efficient and Interpretable Deep Blind Image Deblurring Via Algorithm Unrolling","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2998785217","doi":"https://doi.org/10.1109/tci.2020.2964202","mag":"2998785217"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2020.2964202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2020.2964202","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"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 Computational Imaging","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/A5101506786","display_name":"Yuelong Li","orcid":"https://orcid.org/0000-0001-9927-8691"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuelong Li","raw_affiliation_strings":["Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026535457","display_name":"Mohammad Tofighi","orcid":"https://orcid.org/0000-0002-3249-1399"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammad Tofighi","raw_affiliation_strings":["Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014226370","display_name":"Junyi Geng","orcid":"https://orcid.org/0000-0002-6494-6810"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junyi Geng","raw_affiliation_strings":["Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014013504","display_name":"Vishal Monga","orcid":"https://orcid.org/0000-0002-5100-2263"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishal Monga","raw_affiliation_strings":["Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005913897","display_name":"Yonina C. Eldar","orcid":"https://orcid.org/0000-0003-4358-5304"},"institutions":[{"id":"https://openalex.org/I53964585","display_name":"Weizmann Institute of Science","ror":"https://ror.org/0316ej306","country_code":"IL","type":"education","lineage":["https://openalex.org/I53964585"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Yonina C. Eldar","raw_affiliation_strings":["Department of Electrical Engineering, Faculty of Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel","institution_ids":["https://openalex.org/I53964585"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101506786"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":11.5975,"has_fulltext":false,"cited_by_count":181,"citation_normalized_percentile":{"value":0.98914633,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"666","last_page":"681"},"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/T10688","display_name":"Image and Signal Denoising Methods","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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9955999851226807,"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/deblurring","display_name":"Deblurring","score":0.9440906047821045},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7682791948318481},{"id":"https://openalex.org/keywords/loop-unrolling","display_name":"Loop unrolling","score":0.6800678372383118},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6263181567192078},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5753960609436035},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5316622257232666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5144844055175781},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4986763000488281},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.4861869215965271},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4142824709415436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40176621079444885},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34517228603363037},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.32756519317626953},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.2521674633026123}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9440906047821045},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682791948318481},{"id":"https://openalex.org/C76970557","wikidata":"https://www.wikidata.org/wiki/Q1869750","display_name":"Loop unrolling","level":3,"score":0.6800678372383118},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6263181567192078},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5753960609436035},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5316622257232666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5144844055175781},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4986763000488281},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.4861869215965271},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4142824709415436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40176621079444885},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34517228603363037},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.32756519317626953},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2521674633026123},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2020.2964202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2020.2964202","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"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 Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":104,"referenced_works":["https://openalex.org/W1457323852","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1576854369","https://openalex.org/W1598281290","https://openalex.org/W1604428010","https://openalex.org/W1665214252","https://openalex.org/W1669104078","https://openalex.org/W1686810756","https://openalex.org/W1795014501","https://openalex.org/W1861492603","https://openalex.org/W1906770428","https://openalex.org/W1916935112","https://openalex.org/W1919542679","https://openalex.org/W1976730913","https://openalex.org/W1978333359","https://openalex.org/W1984859941","https://openalex.org/W1987075379","https://openalex.org/W1988446025","https://openalex.org/W1991605728","https://openalex.org/W1995551361","https://openalex.org/W2027231794","https://openalex.org/W2032506791","https://openalex.org/W2034972122","https://openalex.org/W2036682493","https://openalex.org/W2043529138","https://openalex.org/W2045849979","https://openalex.org/W2057477395","https://openalex.org/W2069629287","https://openalex.org/W2092051980","https://openalex.org/W2098535678","https://openalex.org/W2099471712","https://openalex.org/W2099628070","https://openalex.org/W2103913786","https://openalex.org/W2106923440","https://openalex.org/W2110158442","https://openalex.org/W2112796928","https://openalex.org/W2118103795","https://openalex.org/W2121927366","https://openalex.org/W2124964692","https://openalex.org/W2126097106","https://openalex.org/W2132680427","https://openalex.org/W2133665775","https://openalex.org/W2135238609","https://openalex.org/W2140824929","https://openalex.org/W2141115311","https://openalex.org/W2156387975","https://openalex.org/W2161008509","https://openalex.org/W2161804069","https://openalex.org/W2167307343","https://openalex.org/W2167767461","https://openalex.org/W2170608748","https://openalex.org/W2171500271","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2294215176","https://openalex.org/W2300657047","https://openalex.org/W2324369761","https://openalex.org/W2331376995","https://openalex.org/W2346276594","https://openalex.org/W2465552163","https://openalex.org/W2560533888","https://openalex.org/W2574952845","https://openalex.org/W2708797285","https://openalex.org/W2737660901","https://openalex.org/W2738579427","https://openalex.org/W2740543610","https://openalex.org/W2756389006","https://openalex.org/W2759428153","https://openalex.org/W2777194773","https://openalex.org/W2780534972","https://openalex.org/W2782977076","https://openalex.org/W2798735168","https://openalex.org/W2798840374","https://openalex.org/W2902719825","https://openalex.org/W2909370557","https://openalex.org/W2962708058","https://openalex.org/W2962785568","https://openalex.org/W2962835968","https://openalex.org/W2963130865","https://openalex.org/W2963312584","https://openalex.org/W2964030969","https://openalex.org/W2964121744","https://openalex.org/W2972675027","https://openalex.org/W4214815024","https://openalex.org/W4232301379","https://openalex.org/W4236387761","https://openalex.org/W4244769743","https://openalex.org/W4251178070","https://openalex.org/W4254979477","https://openalex.org/W4285719527","https://openalex.org/W4300263211","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6658772490","https://openalex.org/W6677645113","https://openalex.org/W6678856934","https://openalex.org/W6680829993","https://openalex.org/W6682889407","https://openalex.org/W6756241041"],"related_works":["https://openalex.org/W3200192952","https://openalex.org/W4308216825","https://openalex.org/W4312281738","https://openalex.org/W2062923025","https://openalex.org/W3009226622","https://openalex.org/W3015323103","https://openalex.org/W2786875726","https://openalex.org/W4226194415","https://openalex.org/W2008686286","https://openalex.org/W2066650801"],"abstract_inverted_index":{"Blind":[0,136],"image":[1,126],"deblurring":[2,127],"remains":[3],"a":[4,54,84,103,122],"topic":[5],"of":[6,105,147],"enduring":[7],"interest.":[8],"Learning":[9],"based":[10,24,88],"approaches,":[11],"especially":[12],"those":[13,71],"that":[14,63,98,173],"employ":[15],"neural":[16,36,76,85,123],"networks":[17],"have":[18],"emerged":[19],"to":[20,49,75,120,131],"complement":[21],"traditional":[22,107],"model":[23],"methods":[25,178],"and":[26,43,163,179],"in":[27,111,180],"many":[28,176],"cases":[29],"achieve":[30],"vastly":[31],"enhanced":[32],"performance.":[33],"That":[34],"said,":[35],"network":[37,77,86,124,153],"approaches":[38],"are":[39,47,142],"generally":[40],"empirically":[41],"designed":[42],"the":[44,106,112,118,145,166],"underlying":[45],"structures":[46],"difficult":[48],"interpret.":[50],"In":[51,79],"recent":[52],"years,":[53],"promising":[55],"technique":[56],"called":[57],"algorithm":[58,97,119,140],"unrolling":[59],"has":[60,64],"been":[61],"developed":[62],"helped":[65],"connect":[66],"iterative":[67,96],"algorithms":[68],"such":[69],"as":[70,102,132],"for":[72,125,135],"sparse":[73],"coding":[74],"architectures.":[78],"this":[80,90],"article,":[81],"we":[82,129],"propose":[83],"architecture":[87],"on":[89],"idea.":[91],"We":[92,115],"first":[93],"present":[94],"an":[95],"may":[99],"be":[100],"considered":[101],"generalization":[104],"total-variation":[108],"regularization":[109],"method":[110],"gradient":[113],"domain.":[114],"then":[116],"unroll":[117],"construct":[121],"which":[128],"refer":[130],"Deep":[133],"Unrolling":[134],"Deblurring":[137],"(DUBLID).":[138],"Key":[139],"parameters":[141],"learned":[143],"with":[144],"help":[146],"training":[148],"images.":[149],"Our":[150],"proposed":[151],"deep":[152],"DUBLID":[154,174],"achieves":[155],"significant":[156],"practical":[157],"performance":[158],"gains":[159],"while":[160],"enjoying":[161],"interpretability":[162],"efficiency":[164],"at":[165],"same":[167],"time.":[168],"Extensive":[169],"experimental":[170],"results":[171],"show":[172],"outperforms":[175],"state-of-the-art":[177],"addition":[181],"is":[182],"computationally":[183],"faster.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":37},{"year":2023,"cited_by_count":34},{"year":2022,"cited_by_count":34},{"year":2021,"cited_by_count":39},{"year":2020,"cited_by_count":11}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}