{"id":"https://openalex.org/W3179504215","doi":"https://doi.org/10.2352/issn.2470-1173.2021.7.iss-067","title":"Under Display Camera Quad Bayer Raw Image Restoration using Deep Learning","display_name":"Under Display Camera Quad Bayer Raw Image Restoration using Deep Learning","publication_year":2021,"publication_date":"2021-01-18","ids":{"openalex":"https://openalex.org/W3179504215","doi":"https://doi.org/10.2352/issn.2470-1173.2021.7.iss-067","mag":"3179504215"},"language":"en","primary_location":{"id":"doi:10.2352/issn.2470-1173.2021.7.iss-067","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2021.7.iss-067","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/A5107915133","display_name":"Irina Kim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Irina Kim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103226212","display_name":"YunSeok Choi","orcid":"https://orcid.org/0000-0002-9971-1501"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunseok Choi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081943809","display_name":"Hayoung Ko","orcid":"https://orcid.org/0000-0002-1566-9925"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hayoung Ko","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005899399","display_name":"Dongpan Lim","orcid":"https://orcid.org/0000-0002-8615-3088"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dongpan Lim","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108282059","display_name":"Young-Il Seo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Youngil Seo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080727151","display_name":"Jeongguk Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jeongguk Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042798102","display_name":"Geunyoung Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Geunyoung Lee","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044874159","display_name":"Eundoo Heo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eundoo Heo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055528937","display_name":"Seongwook Song","orcid":"https://orcid.org/0000-0003-0517-3958"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seongwook Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102117971","display_name":"SukHwan Lim","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sukhwan Lim","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":1.1212,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80239557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"33","issue":"7","first_page":"67","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11408","display_name":"Advanced Optical Imaging Technologies","score":0.9936000108718872,"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/T11408","display_name":"Advanced Optical Imaging Technologies","score":0.9936000108718872,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9879000186920166,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9850000143051147,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6909946203231812},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.6329479813575745},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6227093935012817},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4967077374458313}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6909946203231812},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.6329479813575745},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6227093935012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4967077374458313}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/issn.2470-1173.2021.7.iss-067","is_oa":false,"landing_page_url":"https://doi.org/10.2352/issn.2470-1173.2021.7.iss-067","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":[{"id":"https://metadata.un.org/sdg/9","score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1891287906","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W2755342338","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2058170566"],"abstract_inverted_index":{"Can":[0],"a":[1,72,115,166],"mobile":[2,18],"camera":[3],"see":[4],"better":[5],"through":[6],"display?":[7],"Under":[8],"Display":[9],"Camera":[10],"(UDC)":[11],"is":[12,94],"the":[13,99],"most":[14],"awaited":[15],"feature":[16],"in":[17,20,71,98,128,188,197],"market":[19],"2020":[21],"enabling":[22],"more":[23],"preferable":[24],"user":[25],"experience,":[26],"however,":[27],"there":[28],"are":[29,41],"technological":[30],"obstacles":[31],"to":[32,43,51,89,95,118,161],"obtain":[33],"acceptable":[34],"UDC":[35,120,129,135],"image":[36,82,91,121,145,189],"quality.":[37],"Mobile":[38],"OLED":[39],"panels":[40],"struggling":[42],"reach":[44],"beyond":[45],"20%":[46],"of":[47,69],"light":[48,57,70],"transmittance,":[49],"leading":[50],"challenging":[52],"capture":[53],"conditions.":[54],"To":[55],"improve":[56,96,119],"sensitivity,":[58],"some":[59],"solutions":[60],"use":[61],"binned":[62],"output":[63],"losing":[64],"spatial":[65],"resolution.":[66],"Optical":[67],"diffraction":[68],"panel":[73],"induces":[74],"contrast":[75],"degradation":[76],"and":[77,107,141,171,182],"various":[78],"visual":[79,177],"artifacts":[80,178],"including":[81,102,179],"ghosts,":[83],"yellowish":[84],"tint":[85],"etc.":[86],"Standard":[87],"approach":[88,117],"address":[90],"quality":[92,122,190],"issues":[93],"blocks":[97,127],"imaging":[100],"pipeline":[101,130,193],"Image":[103],"Signal":[104],"Processor":[105],"(ISP)":[106],"deblur":[108,140],"block.":[109],"In":[110],"this":[111],"work,":[112],"we":[113,124],"propose":[114],"novel":[116],"-":[123,202],"replace":[125],"all":[126],"with":[131,175],"all-in-one":[132],"network":[133,164],"\u2013":[134,194],"d^Net.":[136],"Proposed":[137,163],"solution":[138],"can":[139,172],"reconstruct":[142],"full":[143],"resolution":[144],"directly":[146],"from":[147],"non-Bayer":[148,160],"raw":[149],"image,":[150],"e.g.":[151],"Quad":[152],"Bayer,":[153],"without":[154],"requiring":[155],"remosaic":[156],"algorithm":[157],"that":[158],"rearranges":[159],"Bayer.":[162],"has":[165],"very":[167],"large":[168],"receptive":[169],"field":[170],"easily":[173],"deal":[174],"large-scale":[176],"color":[180],"moir\u00e9":[181],"ghosts.":[183],"Experiments":[184],"show":[185],"significant":[186],"improvement":[187],"vs":[191],"conventional":[192],"over":[195],"4dB":[196],"PSNR":[198],"on":[199],"popular":[200],"benchmark":[201],"Kodak":[203],"dataset.":[204]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
