{"id":"https://openalex.org/W2136910298","doi":"https://doi.org/10.1109/tip.2002.1006401","title":"A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising","display_name":"A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising","publication_year":2002,"publication_date":"2002-05-01","ids":{"openalex":"https://openalex.org/W2136910298","doi":"https://doi.org/10.1109/tip.2002.1006401","mag":"2136910298","pmid":"https://pubmed.ncbi.nlm.nih.gov/18244654"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2002.1006401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2002.1006401","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/A5031078128","display_name":"Aleksandra Pi\u017eurica","orcid":"https://orcid.org/0000-0002-9322-4999"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"A. Pizurica","raw_affiliation_strings":["Department for Telecommunications and Information Processing, Ghent University, B-9000 Gent, Belgium. aleksandra.pizurica@telin.rug.ac.be","Dept. for Telecommun. & Inf. Process. (TELIN), Ghent Univ., Gent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department for Telecommunications and Information Processing, Ghent University, B-9000 Gent, Belgium. aleksandra.pizurica@telin.rug.ac.be","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Dept. for Telecommun. & Inf. Process. (TELIN), Ghent Univ., Gent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071483672","display_name":"Wilfried Philips","orcid":"https://orcid.org/0000-0003-4456-4353"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"W. Philips","raw_affiliation_strings":["Department for Telecommunications and Information Processing (TELIN), Ghent University, Ghent, Belgium","Dept. for Telecommun. & Inf. Process. (TELIN), Ghent Univ., Gent, Belgium"],"affiliations":[{"raw_affiliation_string":"Department for Telecommunications and Information Processing (TELIN), Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"Dept. for Telecommun. & Inf. Process. (TELIN), Ghent Univ., Gent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075006920","display_name":"Ignace Lemahieu","orcid":"https://orcid.org/0000-0002-0894-9988"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"I. Lemahieu","raw_affiliation_strings":["Department for Electronics and Information Systems (ELIS MEDISIP), Ghent University, Ghent, Belgium","[Department for Electronics and Information Systems (ELIS MEDISIP), Ghent University, Ghent, Belgium]"],"affiliations":[{"raw_affiliation_string":"Department for Electronics and Information Systems (ELIS MEDISIP), Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]},{"raw_affiliation_string":"[Department for Electronics and Information Systems (ELIS MEDISIP), Ghent University, Ghent, Belgium]","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030970935","display_name":"Marc Acheroy","orcid":null},"institutions":[{"id":"https://openalex.org/I150517870","display_name":"Royal Military Academy","ror":"https://ror.org/02vmnye06","country_code":"BE","type":"education","lineage":["https://openalex.org/I150517870"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"M. Acheroy","raw_affiliation_strings":["Royal Military Academy, Brussels, Belgium","Royal Military Academy Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Royal Military Academy, Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]},{"raw_affiliation_string":"Royal Military Academy Brussels, Belgium","institution_ids":["https://openalex.org/I150517870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5031078128"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":null,"apc_paid":null,"fwci":8.8364,"has_fulltext":false,"cited_by_count":278,"citation_normalized_percentile":{"value":0.98295517,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":"5","first_page":"545","last_page":"557"},"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":0.9955999851226807,"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":0.986299991607666,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7380596399307251},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6547412276268005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.638317346572876},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5656542181968689},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.545936107635498},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5443030595779419},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5414806008338928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5212031602859497},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.4633885324001312},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.43497923016548157},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4086887836456299},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3445326089859009},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.21384850144386292}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7380596399307251},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6547412276268005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.638317346572876},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5656542181968689},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.545936107635498},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5443030595779419},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5414806008338928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5212031602859497},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.4633885324001312},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.43497923016548157},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4086887836456299},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3445326089859009},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.21384850144386292}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tip.2002.1006401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2002.1006401","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:18244654","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/18244654","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},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.20.2292","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.2292","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://telin.rug.ac.be/~sanja/Papers/TransIP02.pdf","raw_type":"text"},{"id":"pmh:oai:archive.ugent.be:160699","is_oa":false,"landing_page_url":"http://hdl.handle.net/1854/LU-160699","pdf_url":null,"source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1057-7149","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W59771946","https://openalex.org/W123703667","https://openalex.org/W186419298","https://openalex.org/W798527754","https://openalex.org/W1489119587","https://openalex.org/W1500551892","https://openalex.org/W1507028917","https://openalex.org/W1536252645","https://openalex.org/W1667165204","https://openalex.org/W2004217976","https://openalex.org/W2020999234","https://openalex.org/W2036488048","https://openalex.org/W2037384528","https://openalex.org/W2057183507","https://openalex.org/W2057612871","https://openalex.org/W2061052441","https://openalex.org/W2062024414","https://openalex.org/W2065391104","https://openalex.org/W2079724595","https://openalex.org/W2084134149","https://openalex.org/W2101789093","https://openalex.org/W2106200738","https://openalex.org/W2115755118","https://openalex.org/W2124335859","https://openalex.org/W2132984323","https://openalex.org/W2134929491","https://openalex.org/W2136017820","https://openalex.org/W2142542544","https://openalex.org/W2149925139","https://openalex.org/W2152328854","https://openalex.org/W2162560885","https://openalex.org/W2163612361","https://openalex.org/W2168796889","https://openalex.org/W2612218357","https://openalex.org/W2798501834","https://openalex.org/W2942228371","https://openalex.org/W3017143921","https://openalex.org/W4214540058","https://openalex.org/W4240321282","https://openalex.org/W4255272544","https://openalex.org/W4255521522"],"related_works":["https://openalex.org/W2356597680","https://openalex.org/W50079190","https://openalex.org/W2114846443","https://openalex.org/W3102147106","https://openalex.org/W2093471820","https://openalex.org/W2347460059","https://openalex.org/W2126747775","https://openalex.org/W2092834568","https://openalex.org/W2095844239","https://openalex.org/W2077021924"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,11,49,59,76,112,120],"new":[4,16],"wavelet-based":[5],"image":[6,41],"denoising":[7,135],"method,":[8],"which":[9],"extends":[10],"\"geometrical\"":[12],"Bayesian":[13,50],"framework.":[14,51],"The":[15,52,62,80,130],"method":[17],"combines":[18],"three":[19,44,81],"criteria":[20,45,102],"for":[21,103],"distinguishing":[22,104],"supposedly":[23],"useful":[24,105],"coefficients":[25,39,95,106],"from":[26,107],"noise:":[27],"coefficient":[28,66],"magnitudes,":[29],"their":[30,69],"evolution":[31,70],"across":[32,71],"scales":[33,72],"and":[34,68,99,118],"spatial":[35,53],"clustering":[36,54],"of":[37,93],"large":[38],"near":[40],"edges.":[42],"These":[43],"are":[46,56,73,89,96,109],"combined":[47],"in":[48,58,75],"properties":[55,64],"expressed":[57,74],"prior":[60,126],"model.":[61,79],"statistical":[63],"concerning":[65],"magnitudes":[67],"joint":[77,113],"conditional":[78,114],"main":[82],"novelties":[83],"with":[84],"respect":[85],"to":[86],"related":[87,138],"approaches":[88],"(1)":[90],"the":[91],"interscale-ratios":[92],"wavelet":[94],"statistically":[97],"characterized":[98],"different":[100],"local":[101],"noise":[108],"evaluated,":[110],"(2)":[111],"model":[115,127],"is":[116,128],"introduced,":[117],"(3)":[119],"novel":[121],"anisotropic":[122],"Markov":[123],"random":[124],"field":[125],"proposed.":[129],"results":[131],"demonstrate":[132],"an":[133],"improved":[134],"performance":[136],"over":[137],"earlier":[139],"techniques.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":15},{"year":2015,"cited_by_count":18},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":11},{"year":2012,"cited_by_count":12}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
