{"id":"https://openalex.org/W2786322899","doi":"https://doi.org/10.1109/apsipa.2017.8282207","title":"Joint bilateral based image denoising using multi-sized 2D hard threshold","display_name":"Joint bilateral based image denoising using multi-sized 2D hard threshold","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2786322899","doi":"https://doi.org/10.1109/apsipa.2017.8282207","mag":"2786322899"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2017.8282207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101617954","display_name":"Takuro Yamaguchi","orcid":"https://orcid.org/0000-0002-8745-6566"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takuro Yamaguchi","raw_affiliation_strings":["EEE Dept., Keio Univ., Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EEE Dept., Keio Univ., Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090181402","display_name":"Masaaki Ikehara","orcid":"https://orcid.org/0000-0003-3461-1507"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Ikehara","raw_affiliation_strings":["EEE Dept., Keio Univ., Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EEE Dept., Keio Univ., Kanagawa, Japan","institution_ids":["https://openalex.org/I203951103"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I203951103"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.19686213,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1178","last_page":"1181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9975000023841858,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bilateral-filter","display_name":"Bilateral filter","score":0.8287403583526611},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.7014412879943848},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.7010793089866638},{"id":"https://openalex.org/keywords/non-local-means","display_name":"Non-local means","score":0.6669074296951294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6636652946472168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6403930187225342},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5675375461578369},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.5632404685020447},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5585449934005737},{"id":"https://openalex.org/keywords/step-detection","display_name":"Step detection","score":0.5469298362731934},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5320481061935425},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4449484348297119},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.4403155446052551},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4260645806789398},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42358189821243286},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.2692469656467438},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.1679610311985016},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0810878574848175}],"concepts":[{"id":"https://openalex.org/C156140930","wikidata":"https://www.wikidata.org/wiki/Q860417","display_name":"Bilateral filter","level":3,"score":0.8287403583526611},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7014412879943848},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.7010793089866638},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.6669074296951294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6636652946472168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6403930187225342},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5675375461578369},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.5632404685020447},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5585449934005737},{"id":"https://openalex.org/C293773","wikidata":"https://www.wikidata.org/wiki/Q7608015","display_name":"Step detection","level":3,"score":0.5469298362731934},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5320481061935425},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4449484348297119},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.4403155446052551},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4260645806789398},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42358189821243286},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.2692469656467438},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.1679610311985016},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0810878574848175},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.0},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/apsipa.2017.8282207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2017.8282207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1968776821","https://openalex.org/W1998728244","https://openalex.org/W2014311222","https://openalex.org/W2030716039","https://openalex.org/W2037642501","https://openalex.org/W2048695508","https://openalex.org/W2053514113","https://openalex.org/W2097073572","https://openalex.org/W2099244020","https://openalex.org/W2159889048","https://openalex.org/W2160451035","https://openalex.org/W2294560855"],"related_works":["https://openalex.org/W233850645","https://openalex.org/W1998728244","https://openalex.org/W2348643679","https://openalex.org/W2082304850","https://openalex.org/W1699622673","https://openalex.org/W2903172302","https://openalex.org/W4213271663","https://openalex.org/W2078677256","https://openalex.org/W2511423457","https://openalex.org/W2058614856"],"abstract_inverted_index":{"Non-local":[0],"processing":[1,40],"based":[2],"denoising":[3,157],"methods":[4],"obtain":[5,88],"high":[6,12],"quality":[7,154],"outputs.":[8,106],"However,":[9],"they":[10],"have":[11],"calculation":[13,144],"costs":[14],"due":[15],"to":[16,68,155],"the":[17,26,54,79,110,113],"non-local":[18,31,156],"processing.":[19,32],"In":[20],"this":[21],"paper,":[22],"we":[23,52,72,97,108],"focus":[24],"on":[25],"bilateral":[27,34,56,115],"filter":[28,35,41,60,116],"instead":[29],"of":[30,112],"Although":[33],"is":[36,122],"a":[37,74,89,119,142],"traditional":[38],"local":[39],"which":[42,58],"can":[43],"preserve":[44],"edges,":[45],"it":[46],"cannot":[47],"remove":[48],"strong":[49],"noise.":[50],"Therefore,":[51],"utilize":[53,73],"joint":[55,114],"filter,":[57],"calculates":[59],"coefficients":[61,117],"using":[62],"another":[63],"reference":[64],"image.":[65],"For":[66],"adaptation":[67],"single":[69],"image":[70,77,92,95,139],"denoising,":[71],"pre-":[75],"estimated":[76],"by":[78],"hard":[80,100],"threshold":[81,101],"operation":[82,102],"in":[83,123,141],"2D":[84],"frequency":[85],"domain.":[86],"To":[87],"pre-estimated":[90],"noiseless":[91],"while":[93],"preserving":[94,138],"details,":[96],"apply":[98],"multi-sized":[99],"and":[103,146],"aggregate":[104],"their":[105],"Moreover,":[107],"change":[109],"estimation":[111],"whether":[118],"target":[120],"pixel":[121],"an":[124],"edge":[125],"regions":[126],"or":[127],"not.":[128],"By":[129],"these":[130],"improvements,":[131],"our":[132,150],"proposed":[133],"method":[134,151],"removes":[135],"noise":[136],"with":[137],"details":[140],"low":[143],"cost":[145],"experimental":[147],"results":[148],"show":[149],"has":[152],"comparable":[153],"methods.":[158]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}