{"id":"https://openalex.org/W1586998109","doi":"https://doi.org/10.1109/tip.2015.2463220","title":"Bayesian Inference for Neighborhood Filters With Application in Denoising","display_name":"Bayesian Inference for Neighborhood Filters With Application in Denoising","publication_year":2015,"publication_date":"2015-07-30","ids":{"openalex":"https://openalex.org/W1586998109","doi":"https://doi.org/10.1109/tip.2015.2463220","mag":"1586998109","pmid":"https://pubmed.ncbi.nlm.nih.gov/26259244"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2015.2463220","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2463220","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5042036635","display_name":"Chao-Tsung Huang","orcid":"https://orcid.org/0000-0002-9173-520X"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chao-Tsung Huang","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, Taiwan","National Tsing Hua University, , Hsinchu, Taiw\u00e1n"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, Taiwan","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"National Tsing Hua University, , Hsinchu, Taiw\u00e1n","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5042036635"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":1.4175,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.84617008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"24","issue":"11","first_page":"4299","last_page":"4311"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9950000047683716,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9912999868392944,"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/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.7152247428894043},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5501169562339783},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.529651403427124},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.49484699964523315},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47463592886924744},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46613261103630066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45270487666130066},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4351658225059509},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.43451589345932007},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42964085936546326},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4196544587612152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4145032465457916},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3872007727622986},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3679748773574829},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3239792585372925},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15575093030929565},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.10984840989112854}],"concepts":[{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.7152247428894043},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5501169562339783},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.529651403427124},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.49484699964523315},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47463592886924744},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46613261103630066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45270487666130066},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4351658225059509},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.43451589345932007},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42964085936546326},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4196544587612152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4145032465457916},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3872007727622986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3679748773574829},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3239792585372925},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15575093030929565},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.10984840989112854},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2015.2463220","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2463220","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:26259244","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26259244","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7099999785423279,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G3401178649","display_name":"Dragonfly: Algorithm and Prototype Development for Hand-Held Light-Field Camera","funder_award_id":"MOST103-2218-E007-008-MY3","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W14998287","https://openalex.org/W1494195692","https://openalex.org/W1586998109","https://openalex.org/W1652206149","https://openalex.org/W1979139980","https://openalex.org/W1995194116","https://openalex.org/W1998419211","https://openalex.org/W2007165614","https://openalex.org/W2017451354","https://openalex.org/W2019195278","https://openalex.org/W2025242006","https://openalex.org/W2025813857","https://openalex.org/W2034588920","https://openalex.org/W2042680715","https://openalex.org/W2048695508","https://openalex.org/W2054640142","https://openalex.org/W2056370875","https://openalex.org/W2099244020","https://openalex.org/W2108382860","https://openalex.org/W2109991658","https://openalex.org/W2113945798","https://openalex.org/W2116857329","https://openalex.org/W2119938170","https://openalex.org/W2122275806","https://openalex.org/W2123782500","https://openalex.org/W2130582503","https://openalex.org/W2136396015","https://openalex.org/W2139575253","https://openalex.org/W2143131425","https://openalex.org/W2159736423","https://openalex.org/W2160451035","https://openalex.org/W2162053094","https://openalex.org/W2163262991","https://openalex.org/W2536599074","https://openalex.org/W2625633728","https://openalex.org/W4244324388","https://openalex.org/W6677760137"],"related_works":["https://openalex.org/W1839961359","https://openalex.org/W2075146114","https://openalex.org/W2114899076","https://openalex.org/W1783992599","https://openalex.org/W2100805585","https://openalex.org/W2124697778","https://openalex.org/W2135468550","https://openalex.org/W2133422797","https://openalex.org/W2045588782","https://openalex.org/W1976188970"],"abstract_inverted_index":{"Range-weighted":[0],"neighborhood":[1,54],"filters":[2,70],"are":[3,15,145],"useful":[4],"and":[5,11,61,66,76,108,133,158,164,179,187],"popular":[6],"for":[7,32,147],"their":[8],"edge-preserving":[9],"property":[10,34],"simplicity,":[12],"but":[13],"they":[14],"originally":[16],"proposed":[17,58,137,172],"as":[18],"intuitive":[19],"tools.":[20],"Previous":[21],"works":[22],"needed":[23],"to":[24,27,49,59,92,113,124,138],"connect":[25],"them":[26],"other":[28],"tools":[29],"or":[30,36],"models":[31],"indirect":[33],"reasoning":[35],"parameter":[37],"estimation.":[38,79],"In":[39],"this":[40,122],"paper,":[41],"we":[42,120],"introduce":[43],"a":[44,74,148],"unified":[45],"empirical":[46,94],"Bayesian":[47],"framework":[48,123,173],"do":[50],"both":[51],"directly.":[52],"A":[53,130],"noise":[55,165],"model":[56,90,116],"is":[57,111,136],"reason":[60],"infer":[62],"the":[63,81,93,115,125,140,171,180],"Yaroslavsky,":[64],"bilateral,":[65],"modified":[67],"non-local":[68],"means":[69],"by":[71],"joint":[72],"maximum":[73,77],"posteriori":[75],"likelihood":[78],"Then,":[80],"essential":[82],"parameter,":[83],"range":[84,181],"variance,":[85],"can":[86,174,183],"be":[87,184],"estimated":[88,185],"via":[89],"fitting":[91,117,132],"distribution":[95],"of":[96,127,150],"an":[97],"observable":[98],"chi":[99],"scale":[100],"mixture":[101],"variable.":[102],"An":[103],"algorithm":[104],"based":[105],"on":[106],"expectation-maximization":[107],"quasi-Newton":[109],"optimization":[110],"devised":[112],"perform":[114],"efficiently.":[118,188],"Finally,":[119],"apply":[121],"problem":[126],"color-image":[128],"denoising.":[129],"recursive":[131],"filtering":[134],"scheme":[135],"improve":[139],"image":[141],"quality.":[142],"Extensive":[143],"experiments":[144],"performed":[146],"variety":[149],"configurations,":[151],"including":[152],"different":[153],"kernel":[154],"functions,":[155],"filter":[156],"types":[157],"support":[159],"sizes,":[160],"color":[161],"channel":[162],"numbers,":[163],"types.":[166],"The":[167],"results":[168],"show":[169],"that":[170],"fit":[175],"noisy":[176],"images":[177],"well":[178],"variance":[182],"successfully":[186]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2016-06-24T00:00:00"}
