{"id":"https://openalex.org/W4225582194","doi":"https://doi.org/10.2352/ei.2022.34.14.coimg-218","title":"FiveNet: Joint image demosaicing, denoising, deblurring, super-resolution, and clarity enhancement","display_name":"FiveNet: Joint image demosaicing, denoising, deblurring, super-resolution, and clarity enhancement","publication_year":2022,"publication_date":"2022-01-16","ids":{"openalex":"https://openalex.org/W4225582194","doi":"https://doi.org/10.2352/ei.2022.34.14.coimg-218"},"language":"en","primary_location":{"id":"doi:10.2352/ei.2022.34.14.coimg-218","is_oa":true,"landing_page_url":"https://doi.org/10.2352/ei.2022.34.14.coimg-218","pdf_url":"https://library.imaging.org/admin/apis/public/api/ist/website/downloadArticle/ei/34/14/COIMG-218","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":true,"oa_status":"bronze","oa_url":"https://library.imaging.org/admin/apis/public/api/ist/website/downloadArticle/ei/34/14/COIMG-218","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mykola Ponomarenko","orcid":null},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Mykola Ponomarenko","raw_affiliation_strings":["Tampere University, Tampere, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tampere University, Tampere, Finland","institution_ids":["https://openalex.org/I166825849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102981113","display_name":"\u0412. \u0418. \u041c\u0430\u0440\u0447\u0443\u043a","orcid":"https://orcid.org/0000-0001-8576-0081"},"institutions":[{"id":"https://openalex.org/I4210097717","display_name":"Don State Technical University","ror":"https://ror.org/00x5je630","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210097717"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Vladimir Marchuk","raw_affiliation_strings":["Don State Technical University, Rostov-on-Don, Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Don State Technical University, Rostov-on-Don, Russia","institution_ids":["https://openalex.org/I4210097717"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090213299","display_name":"Karen Egiazarian","orcid":"https://orcid.org/0000-0002-8135-1085"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Karen Egiazarian","raw_affiliation_strings":["Tampere University, Tampere, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tampere University, Tampere, Finland","institution_ids":["https://openalex.org/I166825849"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0813,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.30551129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"34","issue":"14","first_page":"218","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9991999864578247,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9988999962806702,"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":0.9499022960662842},{"id":"https://openalex.org/keywords/clarity","display_name":"CLARITY","score":0.7787656784057617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7142439484596252},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6323961019515991},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5869244933128357},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5175915956497192},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.454584002494812},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.41980960965156555},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4142371118068695},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3733495771884918},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.36696627736091614},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3461708426475525}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.9499022960662842},{"id":"https://openalex.org/C2777146004","wikidata":"https://www.wikidata.org/wiki/Q14949826","display_name":"CLARITY","level":2,"score":0.7787656784057617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7142439484596252},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323961019515991},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5869244933128357},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5175915956497192},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.454584002494812},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.41980960965156555},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4142371118068695},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3733495771884918},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.36696627736091614},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3461708426475525},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2352/ei.2022.34.14.coimg-218","is_oa":true,"landing_page_url":"https://doi.org/10.2352/ei.2022.34.14.coimg-218","pdf_url":"https://library.imaging.org/admin/apis/public/api/ist/website/downloadArticle/ei/34/14/COIMG-218","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":{"id":"doi:10.2352/ei.2022.34.14.coimg-218","is_oa":true,"landing_page_url":"https://doi.org/10.2352/ei.2022.34.14.coimg-218","pdf_url":"https://library.imaging.org/admin/apis/public/api/ist/website/downloadArticle/ei/34/14/COIMG-218","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"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6444257319","display_name":null,"funder_award_id":"075-15-","funder_id":"https://openalex.org/F4320327494","funder_display_name":"Ministry of Science and Higher Education of the Russian Federation"}],"funders":[{"id":"https://openalex.org/F4320327494","display_name":"Ministry of Science and Higher Education of the Russian Federation","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4225582194.pdf","grobid_xml":"https://content.openalex.org/works/W4225582194.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1984066865","https://openalex.org/W1994829098","https://openalex.org/W2005188790","https://openalex.org/W2011245511","https://openalex.org/W2116765143","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2155437183","https://openalex.org/W2194775991","https://openalex.org/W2508457857","https://openalex.org/W2513500606","https://openalex.org/W2622470254","https://openalex.org/W2735224642","https://openalex.org/W2741137940","https://openalex.org/W2832157980","https://openalex.org/W2890853274","https://openalex.org/W2963372104","https://openalex.org/W2963725279","https://openalex.org/W2970318705","https://openalex.org/W2995489114","https://openalex.org/W3033543121","https://openalex.org/W3035595647","https://openalex.org/W3035712445","https://openalex.org/W3081639259","https://openalex.org/W3091249416","https://openalex.org/W3103100299","https://openalex.org/W3176469911","https://openalex.org/W4287682995","https://openalex.org/W6687483927","https://openalex.org/W7020533926"],"related_works":["https://openalex.org/W2099770336","https://openalex.org/W2140617750","https://openalex.org/W2094238738","https://openalex.org/W3137059050","https://openalex.org/W2008178540","https://openalex.org/W4365152410","https://openalex.org/W2132132164","https://openalex.org/W2906703443","https://openalex.org/W2080322084","https://openalex.org/W2787706201"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,144],"convolutional":[4],"neural":[5],"network":[6,20,58],"for":[7,119,154],"joint":[8],"image":[9,26,86,134,148],"demosaicing,":[10],"denoising,":[11],"deblurring,":[12],"super-resolution":[13],"and":[14,31,48,106,151],"clarity":[15,49,77,104,129,156],"enhancement":[16,78,130,157],"is":[17,53,72,108],"proposed.":[18],"The":[19,125],"inputs":[21],"are":[22,123],"four-channel":[23],"Bayer":[24],"CFA":[25],"(R,":[27],"G,":[28,29],"B)":[30],"three":[32],"channels":[33],"of":[34,67,99],"the":[35,56,65,80,120,141,155],"same":[36],"size":[37],"containing":[38],"distortions":[39],"maps,":[40],"namely,":[41],"noise":[42],"level":[43,46],"map,":[44,47],"blur":[45],"degradation":[50],"map.":[51],"It":[52,71],"shown":[54],"that":[55,75,128],"designed":[57,109],"FiveNet":[59],"can":[60,83,131],"effectively":[61],"process":[62],"images":[63,101,111],"with":[64,102],"mix":[66],"five":[68],"different":[69,103],"distortions.":[70],"also":[73],"demonstrated":[74],"adding":[76],"into":[79],"processing":[81],"chain":[82],"additionally":[84],"increase":[85,133],"quality":[87,149],"(by":[88],"up":[89],"to":[90],"3-4":[91],"dB":[92],"in":[93],"PSNR).":[94],"A":[95,137],"small":[96],"dataset":[97],"ClarityDegr120":[98],"color":[100],"degradations":[105],"enhancements":[107],"using":[110,140],"processed":[112],"by":[113],"FiveNet.":[114],"Mean":[115],"opinion":[116],"scores":[117],"(MOS)":[118],"test":[121],"set":[122],"collected.":[124],"MOS":[126,142],"prove":[127],"significantly":[132],"visual":[135],"quality.":[136],"comparative":[138],"analysis":[139],"demonstrates":[143],"low":[145],"correspondence":[146],"between":[147],"metrics":[150],"human":[152],"perception":[153],"task.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
