{"id":"https://openalex.org/W4312620360","doi":"https://doi.org/10.1109/cvpr52688.2022.00580","title":"Pixel screening based intermediate correction for blind deblurring","display_name":"Pixel screening based intermediate correction for blind deblurring","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4312620360","doi":"https://doi.org/10.1109/cvpr52688.2022.00580"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.00580","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5101594718","display_name":"Meina Zhang","orcid":"https://orcid.org/0000-0003-4884-0554"},"institutions":[{"id":"https://openalex.org/I4210145278","display_name":"Institute of Applied Physics and Computational Mathematics","ror":"https://ror.org/03sxpbt26","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meina Zhang","raw_affiliation_strings":["Institute of Applied Physics and Computational Mathematics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Applied Physics and Computational Mathematics, Beijing, China","institution_ids":["https://openalex.org/I4210145278"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085166013","display_name":"Yingying Fang","orcid":"https://orcid.org/0000-0001-6334-8635"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yingying Fang","raw_affiliation_strings":["Imperial College London, London, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, United Kingdom","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027216125","display_name":"Guoxi Ni","orcid":"https://orcid.org/0000-0002-1605-5095"},"institutions":[{"id":"https://openalex.org/I4210145278","display_name":"Institute of Applied Physics and Computational Mathematics","ror":"https://ror.org/03sxpbt26","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxi Ni","raw_affiliation_strings":["Institute of Applied Physics and Computational Mathematics, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Applied Physics and Computational Mathematics, Beijing, China","institution_ids":["https://openalex.org/I4210145278"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059443966","display_name":"Tieyong Zeng","orcid":"https://orcid.org/0000-0002-0688-202X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tieyong Zeng","raw_affiliation_strings":["The Chinese University of Hong Kong, Shatin, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shatin, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.95,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.681005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.999,"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":0.999,"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":0.995,"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"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9863,"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/deblurring","display_name":"Deblurring","score":0.97924197},{"id":"https://openalex.org/keywords/latent-image","display_name":"Latent image","score":0.74504167},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7391623},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.59774137},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization","score":0.55923927},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5174973}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.97924197},{"id":"https://openalex.org/C205372313","wikidata":"https://www.wikidata.org/wiki/Q355645","display_name":"Latent image","level":3,"score":0.74504167},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7391623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6953732},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.65446806},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6111803},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.59774137},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.55923927},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5174973},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48830843},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.47229034},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4448971},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37226316},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24070263},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.22033969},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.091615796},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52688.2022.00580","pdf_url":null,"source":{"id":"https://openalex.org/S4363607701","display_name":"2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":38,"referenced_works":["https://openalex.org/W1598281290","https://openalex.org/W1604428010","https://openalex.org/W1972406935","https://openalex.org/W1976730913","https://openalex.org/W1978333359","https://openalex.org/W1987075379","https://openalex.org/W1992309968","https://openalex.org/W1994321112","https://openalex.org/W2030108224","https://openalex.org/W2036682493","https://openalex.org/W2047123483","https://openalex.org/W2135238609","https://openalex.org/W2161804069","https://openalex.org/W2167307343","https://openalex.org/W2187997753","https://openalex.org/W2331376995","https://openalex.org/W233979554","https://openalex.org/W2461759225","https://openalex.org/W2465552163","https://openalex.org/W2472069500","https://openalex.org/W2474628748","https://openalex.org/W2737660901","https://openalex.org/W2740543610","https://openalex.org/W2776707568","https://openalex.org/W2777685367","https://openalex.org/W2894555492","https://openalex.org/W2955179830","https://openalex.org/W2965300963","https://openalex.org/W2967273822","https://openalex.org/W2973468176","https://openalex.org/W3003954661","https://openalex.org/W3034724715","https://openalex.org/W3096970131","https://openalex.org/W3110031215","https://openalex.org/W3144455176","https://openalex.org/W3170697543","https://openalex.org/W3179805570","https://openalex.org/W3182557492"],"related_works":["https://openalex.org/W4385800852","https://openalex.org/W3048764160","https://openalex.org/W3023581765","https://openalex.org/W2965300963","https://openalex.org/W2900701534","https://openalex.org/W2740214449","https://openalex.org/W2521703860","https://openalex.org/W2511945569","https://openalex.org/W2247925651","https://openalex.org/W2060018053"],"abstract_inverted_index":{"Blind":[0],"deblurring":[1,14],"has":[2],"attracted":[3],"much":[4],"interest":[5],"with":[6,50,69],"its":[7],"wide":[8],"applications":[9],"in":[10],"reality.":[11],"The":[12],"blind":[13],"problem":[15],"is":[16],"usually":[17],"solved":[18],"by":[19,54,135],"estimating":[20],"the":[21,25,34,38,59,95,115,121,124,129],"intermediate":[22,26,48,83,96],"kernel":[23,36,108,127],"and":[24,73,98,138],"image":[27,84,97],"alternatively,":[28],"which":[29,87],"will":[30],"finally":[31],"converge":[32],"to":[33,46,92,103],"blurring":[35],"of":[37,123],"observed":[39],"image.":[40],"Numerous":[41],"works":[42],"have":[43,112],"been":[44],"proposed":[45,116],"obtain":[47],"images":[49,70],"fewer":[51],"undesirable":[52],"artifacts":[53],"designing":[55],"delicate":[56],"regularization":[57],"on":[58,132],"latent":[60],"solution.":[61],"However,":[62],"these":[63],"methods":[64,131],"still":[65],"fail":[66],"while":[67],"dealing":[68],"containing":[71],"saturations":[72],"large":[74],"blurs.":[75],"To":[76],"address":[77],"this":[78],"problem,":[79],"we":[80],"propose":[81],"an":[82],"correction":[85],"method":[86,117],"utilizes":[88],"Bayes":[89],"posterior":[90],"estimation":[91],"screen":[93],"through":[94],"exclude":[99],"those":[100],"unfavorable":[101],"pixels":[102],"reduce":[104],"their":[105],"influence":[106],"for":[107],"estimation.":[109],"Extensive":[110],"experiments":[111],"proved":[113],"that":[114],"can":[118],"effectively":[119],"improve":[120],"accuracy":[122],"final":[125],"derived":[126],"against":[128],"state-of-the-art":[130],"benchmark":[133],"datasets":[134],"both":[136],"quantitative":[137],"qualitative":[139],"comparisons.":[140]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4312620360","counts_by_year":[{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":7}],"updated_date":"2025-01-08T03:41:51.859774","created_date":"2023-01-05"}