{"id":"https://openalex.org/W3088949656","doi":"https://doi.org/10.2352/issn.2470-1173.2020.10.ipas-181","title":"Non-Blind Image Deconvolution Based on “Ringing” Removal Using Convolutional Neural Network","display_name":"Non-Blind Image Deconvolution Based on “Ringing” Removal Using Convolutional Neural Network","publication_year":2020,"publication_date":"2020-01-26","ids":{"openalex":"https://openalex.org/W3088949656","doi":"https://doi.org/10.2352/issn.2470-1173.2020.10.ipas-181","mag":"3088949656"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2020.10.ipas-181","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2020.10.ipas-181","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic 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/A5112656466","display_name":"Takahiro Kudo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takahiro Kudo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052510171","display_name":"Takanori Fujisawa","orcid":"https://orcid.org/0000-0001-7632-5846"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takanori Fujisawa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101617954","display_name":"Takuro Yamaguchi","orcid":"https://orcid.org/0000-0002-8745-6566"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takuro Yamaguchi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090181402","display_name":"Masaaki Ikehara","orcid":"https://orcid.org/0000-0003-3461-1507"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Masaaki Ikehara","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1115,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.51177937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"32","issue":"10","first_page":"181","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9855999946594238,"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"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9855999946594238,"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":0.9711999893188477,"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":0.8659880757331848},{"id":"https://openalex.org/keywords/ringing","display_name":"Ringing","score":0.7954367399215698},{"id":"https://openalex.org/keywords/deconvolution","display_name":"Deconvolution","score":0.7696164846420288},{"id":"https://openalex.org/keywords/blind-deconvolution","display_name":"Blind deconvolution","score":0.7517399787902832},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7465987801551819},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.722944974899292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6934605836868286},{"id":"https://openalex.org/keywords/ringing-artifacts","display_name":"Ringing artifacts","score":0.594409167766571},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5763824582099915},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5681706070899963},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4451853632926941},{"id":"https://openalex.org/keywords/wiener-deconvolution","display_name":"Wiener deconvolution","score":0.44073039293289185},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.3381667733192444},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.252292275428772},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24788373708724976}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.8659880757331848},{"id":"https://openalex.org/C30684385","wikidata":"https://www.wikidata.org/wiki/Q176509","display_name":"Ringing","level":3,"score":0.7954367399215698},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.7696164846420288},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.7517399787902832},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7465987801551819},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.722944974899292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6934605836868286},{"id":"https://openalex.org/C17828673","wikidata":"https://www.wikidata.org/wiki/Q7334899","display_name":"Ringing artifacts","level":3,"score":0.594409167766571},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5763824582099915},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5681706070899963},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4451853632926941},{"id":"https://openalex.org/C15652857","wikidata":"https://www.wikidata.org/wiki/Q599016","display_name":"Wiener deconvolution","level":4,"score":0.44073039293289185},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.3381667733192444},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.252292275428772},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24788373708724976},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2020.10.ipas-181","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2020.10.ipas-181","pdf_url":null,"source":{"id":"https://openalex.org/S4210227276","display_name":"Electronic Imaging","issn_l":"2470-1173","issn":["2470-1173"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1121716750","https://openalex.org/W2754775787","https://openalex.org/W2022101081","https://openalex.org/W2766867318","https://openalex.org/W2061562117","https://openalex.org/W2090956370","https://openalex.org/W3008080101","https://openalex.org/W2343807919","https://openalex.org/W791927757","https://openalex.org/W2566126253"],"abstract_inverted_index":{"Image":[0],"deconvolution":[1,18,90],"has":[2,9,45,108],"been":[3,46],"an":[4],"important":[5],"issue":[6],"recently.":[7],"It":[8],"two":[10],"kinds":[11,169],"of":[12,23,76,156,170],"approaches:":[13],"non-blind":[14,49,89],"and":[15,33,70,125,173,185],"blind.":[16],"Non-blind":[17],"is":[19,31,114,119,133,138,146],"a":[20,88,94,103],"classic":[21],"problem":[22],"image":[24,161],"deblurring,":[25],"which":[26],"assumes":[27],"that":[28,96,115,134,147],"the":[29,74,80,129,135,142,150,154,160],"PSF":[30],"known":[32],"does":[34,71],"not":[35,72],"change":[36],"universally":[37],"in":[38,79,102,128],"space.":[39],"Recently,":[40],"Convolutional":[41],"Neural":[42],"Network":[43],"(CNN)":[44],"used":[47,167],"for":[48,58],"deconvolution.":[50],"Though":[51],"CNNs":[52],"can":[53,65,97],"deal":[54],"with":[55],"complex":[56],"changes":[57],"unknown":[59],"images,":[60],"some":[61],"CNN-based":[62],"conventional":[63],"methods":[64],"only":[66],"handle":[67],"small":[68,126],"PSFs":[69,78,172],"consider":[73],"use":[75],"large":[77,99,124,157,171],"real":[81],"world.":[82],"In":[83,163],"this":[84],"paper":[85],"we":[86,148,166],"propose":[87],"framework":[91],"based":[92],"on":[93,159],"CNN":[95],"remove":[98],"scale":[100],"ringing":[101,158],"deblurred":[104],"image.":[105,130],"Our":[106],"method":[107,182],"three":[109,168],"key":[110],"points.":[111],"The":[112,131,144],"first":[113],"our":[116,164,181],"network":[117],"architecture":[118],"able":[120,175],"to":[121,140,152,176],"preserve":[122,141],"both":[123,183],"features":[127],"second":[132],"training":[136],"dataset":[137],"created":[139],"details.":[143],"third":[145],"extend":[149],"images":[151],"minimize":[153],"effects":[155],"borders.":[162],"experiments,":[165],"were":[174],"observe":[177],"high-precision":[178],"results":[179],"from":[180],"quantitatively":[184],"qualitatively.":[186]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}