{"id":"https://openalex.org/W2726824826","doi":"https://doi.org/10.1109/icip.2017.8296772","title":"A multi-layer image representation using regularized residual quantization: Application to compression and denoising","display_name":"A multi-layer image representation using regularized residual quantization: Application to compression and denoising","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2726824826","doi":"https://doi.org/10.1109/icip.2017.8296772","mag":"2726824826"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296772","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1707.02194","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062194509","display_name":"Sohrab Ferdowsi","orcid":"https://orcid.org/0000-0003-3768-6408"},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]}],"countries":["CH"],"is_corresponding":true,"raw_author_name":"Sohrab Ferdowsi","raw_affiliation_strings":["Department of Computer Science, University of Geneva, Switzerland","[Department of Computer Science, University of Geneva, Switzerland]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]},{"raw_affiliation_string":"[Department of Computer Science, University of Geneva, Switzerland]","institution_ids":["https://openalex.org/I114457229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091506990","display_name":"Slava Voloshynovskiy","orcid":"https://orcid.org/0000-0003-0416-9674"},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Slava Voloshynovskiy","raw_affiliation_strings":["Department of Computer Science, University of Geneva, Switzerland","[Department of Computer Science, University of Geneva, Switzerland]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]},{"raw_affiliation_string":"[Department of Computer Science, University of Geneva, Switzerland]","institution_ids":["https://openalex.org/I114457229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002437842","display_name":"Dimche Kostadinov","orcid":"https://orcid.org/0009-0001-9000-2370"},"institutions":[{"id":"https://openalex.org/I114457229","display_name":"University of Geneva","ror":"https://ror.org/01swzsf04","country_code":"CH","type":"education","lineage":["https://openalex.org/I114457229"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Dimche Kostadinov","raw_affiliation_strings":["Department of Computer Science, University of Geneva, Switzerland","[Department of Computer Science, University of Geneva, Switzerland]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Geneva, Switzerland","institution_ids":["https://openalex.org/I114457229"]},{"raw_affiliation_string":"[Department of Computer Science, University of Geneva, Switzerland]","institution_ids":["https://openalex.org/I114457229"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062194509"],"corresponding_institution_ids":["https://openalex.org/I114457229"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07354426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"2697","last_page":"2701"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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"}},"topics":[{"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9994999766349792,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9980000257492065,"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/codebook","display_name":"Codebook","score":0.7864229679107666},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5846600532531738},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5761053562164307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.573737621307373},{"id":"https://openalex.org/keywords/codec","display_name":"Codec","score":0.5730284452438354},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5330091118812561},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5328273177146912},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5312694311141968},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.49619966745376587},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.49078139662742615},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.48324403166770935},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4453071653842926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42589807510375977},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3990537226200104},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3347824811935425},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.28897202014923096},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.28652629256248474},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.0676645040512085}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.7864229679107666},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5846600532531738},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5761053562164307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.573737621307373},{"id":"https://openalex.org/C161765866","wikidata":"https://www.wikidata.org/wiki/Q184748","display_name":"Codec","level":2,"score":0.5730284452438354},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5330091118812561},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5328273177146912},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5312694311141968},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.49619966745376587},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.49078139662742615},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.48324403166770935},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4453071653842926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42589807510375977},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3990537226200104},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3347824811935425},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28897202014923096},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28652629256248474},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0676645040512085},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2017.8296772","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296772","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1707.02194","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1707.02194","pdf_url":"https://arxiv.org/pdf/1707.02194","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2726824826","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1707.02194.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1707.02194","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1707.02194","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1707.02194","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1707.02194","pdf_url":"https://arxiv.org/pdf/1707.02194","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1634005169","https://openalex.org/W1970491336","https://openalex.org/W1972959470","https://openalex.org/W2008732654","https://openalex.org/W2053395738","https://openalex.org/W2064408165","https://openalex.org/W2098929365","https://openalex.org/W2122911643","https://openalex.org/W2123921160","https://openalex.org/W2124509324","https://openalex.org/W2141089030","https://openalex.org/W2160547390","https://openalex.org/W2163398148","https://openalex.org/W3102148777","https://openalex.org/W4206310440"],"related_works":["https://openalex.org/W2069472269","https://openalex.org/W2032732069","https://openalex.org/W2114220180","https://openalex.org/W2141460024","https://openalex.org/W2366568653","https://openalex.org/W1972991661","https://openalex.org/W2471140398","https://openalex.org/W1563157624","https://openalex.org/W1889847144","https://openalex.org/W2920971926","https://openalex.org/W2727582110","https://openalex.org/W2370526743","https://openalex.org/W1992648242","https://openalex.org/W1593606211","https://openalex.org/W3019920962","https://openalex.org/W2011811201","https://openalex.org/W2099586185","https://openalex.org/W2274609531","https://openalex.org/W2045811742","https://openalex.org/W2082672733"],"abstract_inverted_index":{"A":[0],"learning-based":[1],"framework":[2,77],"for":[3,110,164,168],"representation":[4],"of":[5,53,82,102,142,152],"domain-specific":[6],"images":[7,29,42,71,131,154],"is":[8,37,78,98,158],"proposed":[9,76],"where":[10,87],"joint":[11],"compression":[12,35,165],"and":[13,133,155,166],"denoising":[14],"can":[15],"be":[16],"done":[17,147],"using":[18],"a":[19,31,44,79,121],"VQ-based":[20],"multi-layer":[21],"network.":[22],"While":[23],"it":[24,58],"learns":[25],"to":[26,128,137,139],"compress":[27,129],"the":[28,34,54,64,69,73,83,91,95,106,118,130,135,149,156,161],"from":[30,43,61,94,105,120],"training":[32],"set,":[33,56],"performance":[36],"very":[38],"well":[39],"generalized":[40],"on":[41,148],"test":[45,55,70],"set.":[46],"Moreover,":[47],"when":[48],"fed":[49],"with":[50,160],"noisy":[51],"versions":[52],"since":[57],"has":[59],"priors":[60],"clean":[62],"images,":[63],"network":[65],"also":[66],"efficiently":[67],"denoises":[68],"during":[72],"reconstruction.":[74],"The":[75,144],"regularized":[80,125],"version":[81],"Residual":[84],"Quantization":[85],"(RQ)":[86],"at":[88],"each":[89],"stage,":[90],"quantization":[92],"error":[93],"previous":[96],"stage":[97],"further":[99],"quantized.":[100],"Instead":[101],"codebook":[103],"learning":[104],"k-means":[107],"which":[108],"over-trains":[109],"high-dimensional":[111],"vectors,":[112],"we":[113],"show":[114],"that":[115],"only":[116],"generating":[117],"codewords":[119],"random,":[122],"but":[123],"properly":[124],"distribution":[126],"suffices":[127],"globally":[132],"without":[134],"need":[136],"resort":[138],"patch-based":[140],"division":[141],"images.":[143],"experiments":[145],"are":[146],"CroppedYale-B":[150],"set":[151],"facial":[153],"method":[157],"compared":[159],"JPEG-2000":[162],"codec":[163],"BM3D":[167],"denoising,":[169],"showing":[170],"promising":[171],"results.":[172]},"counts_by_year":[],"updated_date":"2026-03-21T08:13:44.787528","created_date":"2022-08-05T00:00:00"}
