{"id":"https://openalex.org/W2070582683","doi":"https://doi.org/10.1109/icip.2013.6738226","title":"A Bayesian approach for natural image denoising","display_name":"A Bayesian approach for natural image denoising","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2070582683","doi":"https://doi.org/10.1109/icip.2013.6738226","mag":"2070582683"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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/A5031554273","display_name":"Jordi Salvador","orcid":"https://orcid.org/0000-0002-1809-651X"},"institutions":[{"id":"https://openalex.org/I2929663463","display_name":"Technicolor (Germany)","ror":"https://ror.org/00besvm65","country_code":"DE","type":"company","lineage":["https://openalex.org/I2929663463","https://openalex.org/I4210121266"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jordi Salvador","raw_affiliation_strings":["Image Processing Lab Technicolor R&I Hannover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Lab Technicolor R&I Hannover","institution_ids":["https://openalex.org/I2929663463"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024207929","display_name":"Malte Borsum","orcid":null},"institutions":[{"id":"https://openalex.org/I2929663463","display_name":"Technicolor (Germany)","ror":"https://ror.org/00besvm65","country_code":"DE","type":"company","lineage":["https://openalex.org/I2929663463","https://openalex.org/I4210121266"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Malte Borsum","raw_affiliation_strings":["Image Processing Lab Technicolor R&I Hannover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Lab Technicolor R&I Hannover","institution_ids":["https://openalex.org/I2929663463"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025322156","display_name":"Axel Kochale","orcid":null},"institutions":[{"id":"https://openalex.org/I2929663463","display_name":"Technicolor (Germany)","ror":"https://ror.org/00besvm65","country_code":"DE","type":"company","lineage":["https://openalex.org/I2929663463","https://openalex.org/I4210121266"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Axel Kochale","raw_affiliation_strings":["Image Processing Lab Technicolor R&I Hannover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Image Processing Lab Technicolor R&I Hannover","institution_ids":["https://openalex.org/I2929663463"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2929663463"],"apc_list":null,"apc_paid":null,"fwci":0.2079,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.47576277,"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":"1095","last_page":"1099"},"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":0.9958999752998352,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.989300012588501,"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/parametric-statistics","display_name":"Parametric statistics","score":0.6740242838859558},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6429007053375244},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.629269003868103},{"id":"https://openalex.org/keywords/image-denoising","display_name":"Image denoising","score":0.6259015798568726},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5993531942367554},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.549432635307312},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.5334283113479614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5137568712234497},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5104612112045288},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4778320789337158},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41474953293800354},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38856637477874756},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37619760632514954},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26729047298431396},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08963221311569214}],"concepts":[{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6740242838859558},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6429007053375244},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.629269003868103},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.6259015798568726},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5993531942367554},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.549432635307312},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.5334283113479614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5137568712234497},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5104612112045288},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4778320789337158},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41474953293800354},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38856637477874756},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37619760632514954},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26729047298431396},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08963221311569214}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","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":15,"referenced_works":["https://openalex.org/W2027898483","https://openalex.org/W2037133587","https://openalex.org/W2056370875","https://openalex.org/W2068015987","https://openalex.org/W2083609718","https://openalex.org/W2095106682","https://openalex.org/W2100556411","https://openalex.org/W2103559027","https://openalex.org/W2110158442","https://openalex.org/W2112391032","https://openalex.org/W2150120413","https://openalex.org/W2153663612","https://openalex.org/W2160459408","https://openalex.org/W2168745297","https://openalex.org/W2169899245"],"related_works":["https://openalex.org/W2895947835","https://openalex.org/W4287876945","https://openalex.org/W2087258800","https://openalex.org/W2810018092","https://openalex.org/W3209466624","https://openalex.org/W2387428419","https://openalex.org/W1581044291","https://openalex.org/W2098237619","https://openalex.org/W1974034585","https://openalex.org/W2386722878"],"abstract_inverted_index":{"This":[0,20],"article":[1],"presents":[2],"a":[3,57,71],"new":[4],"method":[5,21,55,84],"for":[6],"estimating":[7,37],"the":[8,34,48,62],"latent":[9],"noiseless":[10],"version":[11],"of":[12,64],"an":[13,44],"observed":[14],"image":[15,39],"corrupted":[16],"by":[17,32],"additive":[18],"noise.":[19],"stems":[22],"from":[23],"classical":[24],"models":[25],"in":[26],"parametric":[27,66,93],"denoising":[28,67],"and":[29,41,69,94],"extends":[30],"them":[31],"modeling":[33],"likelihood":[35],"term,":[36],"adaptive":[38,45],"priors":[40],"automatically":[42],"choosing":[43],"equivalent":[46],"to":[47,60,74,87],"typically":[49],"hand-tuned":[50],"regularization":[51],"constant.":[52],"The":[53,78],"proposed":[54],"introduces":[56],"possible":[58],"path":[59],"overcome":[61],"limitations":[63],"current":[65],"algorithms":[68],"provides":[70],"competitive":[72],"alternative":[73],"powerful":[75],"non-parametric":[76,95],"ones.":[77],"experimental":[79],"results":[80],"show":[81],"how":[82],"our":[83],"adapts":[85],"better":[86],"different":[88],"noise":[89],"types":[90],"than":[91],"state-of-the-art":[92],"algorithms.":[96]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
