{"id":"https://openalex.org/W2147704231","doi":"https://doi.org/10.1109/iscas.2005.1465183","title":"Image Multi-Noise Removal by Wavelet-Based Bayesian Estimator","display_name":"Image Multi-Noise Removal by Wavelet-Based Bayesian Estimator","publication_year":2005,"publication_date":"2005-07-27","ids":{"openalex":"https://openalex.org/W2147704231","doi":"https://doi.org/10.1109/iscas.2005.1465183","mag":"2147704231"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2005.1465183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2005.1465183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2005 IEEE International Symposium on Circuits and Systems","raw_type":"proceedings-article"},"type":"article","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/A5101637706","display_name":"Xu Huang","orcid":"https://orcid.org/0000-0003-3059-4180"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"X. Huang","raw_affiliation_strings":["School of Information Sciences and Engineering, University of Canberra, ACT, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information Sciences and Engineering, University of Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084805389","display_name":"Allan C. Madoc","orcid":null},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A.C. Madoc","raw_affiliation_strings":["Center for Actuarial Studies, Department of Economics, University of Melbourne, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"Center for Actuarial Studies, Department of Economics, University of Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067337334","display_name":"A.D. Cheetham","orcid":null},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A.D. Cheetham","raw_affiliation_strings":["School of Information Sciences and Engineering, University of Canberra, ACT, Australia"],"affiliations":[{"raw_affiliation_string":"School of Information Sciences and Engineering, University of Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101637706"],"corresponding_institution_ids":["https://openalex.org/I188329596"],"apc_list":null,"apc_paid":null,"fwci":0.8954,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78136346,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2699","last_page":"2702"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13487","display_name":"Statistical and numerical algorithms","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/shot-noise","display_name":"Shot noise","score":0.7668700814247131},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.7342972755432129},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.5690876245498657},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5502601861953735},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5097017288208008},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.5046254396438599},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4979078769683838},{"id":"https://openalex.org/keywords/poisson-distribution","display_name":"Poisson distribution","score":0.493764728307724},{"id":"https://openalex.org/keywords/noise-measurement","display_name":"Noise measurement","score":0.45066770911216736},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43521666526794434},{"id":"https://openalex.org/keywords/impulse-noise","display_name":"Impulse noise","score":0.4348742365837097},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.41428086161613464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39607205986976624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39369845390319824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3897255063056946},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.35282325744628906},{"id":"https://openalex.org/keywords/noise-floor","display_name":"Noise floor","score":0.33259230852127075},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.21271508932113647},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10969886183738708},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10753661394119263}],"concepts":[{"id":"https://openalex.org/C72659945","wikidata":"https://www.wikidata.org/wiki/Q1503574","display_name":"Shot noise","level":3,"score":0.7668700814247131},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.7342972755432129},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.5690876245498657},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5502601861953735},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5097017288208008},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.5046254396438599},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4979078769683838},{"id":"https://openalex.org/C100906024","wikidata":"https://www.wikidata.org/wiki/Q205692","display_name":"Poisson distribution","level":2,"score":0.493764728307724},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.45066770911216736},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43521666526794434},{"id":"https://openalex.org/C127372701","wikidata":"https://www.wikidata.org/wiki/Q16979398","display_name":"Impulse noise","level":3,"score":0.4348742365837097},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.41428086161613464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39607205986976624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39369845390319824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3897255063056946},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.35282325744628906},{"id":"https://openalex.org/C187612029","wikidata":"https://www.wikidata.org/wiki/Q17083130","display_name":"Noise floor","level":4,"score":0.33259230852127075},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.21271508932113647},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10969886183738708},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10753661394119263},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iscas.2005.1465183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2005.1465183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2005 IEEE International Symposium on Circuits and Systems","raw_type":"proceedings-article"},{"id":"pmh:tle:548e9d1d-e234-dc06-7ffb-29889fab8b4e:1f071524-0ffb-45dd-b0fd-e2ac8222ffc2:1","is_oa":false,"landing_page_url":"http://www.canberra.edu.au/researchrepository/items/548e9d1d-e234-dc06-7ffb-29889fab8b4e/1/","pdf_url":null,"source":{"id":"https://openalex.org/S7407050591","display_name":"University of Canberra Research Portal","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320992","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W191129667","https://openalex.org/W1569906308","https://openalex.org/W1571229927","https://openalex.org/W1703680408","https://openalex.org/W1985806087","https://openalex.org/W1996124770","https://openalex.org/W1997043932","https://openalex.org/W2085927826","https://openalex.org/W2100874022","https://openalex.org/W2113477595","https://openalex.org/W2127670157","https://openalex.org/W2136017820","https://openalex.org/W2146842127","https://openalex.org/W2149366427","https://openalex.org/W2149925139","https://openalex.org/W2158940042","https://openalex.org/W2163743295","https://openalex.org/W4214806317","https://openalex.org/W6634121937","https://openalex.org/W6659301889","https://openalex.org/W6683518453"],"related_works":["https://openalex.org/W2394151061","https://openalex.org/W2980586888","https://openalex.org/W2081933987","https://openalex.org/W2144975018","https://openalex.org/W2935891649","https://openalex.org/W1160433918","https://openalex.org/W3114722801","https://openalex.org/W2082281026","https://openalex.org/W2369770188","https://openalex.org/W2165141499"],"abstract_inverted_index":{"Images":[0],"are":[1,9,19,54,79,171],"in":[2,15,36,129],"many":[3],"cases":[4],"degraded":[5],"even":[6],"before":[7],"they":[8],"encoded.":[10],"The":[11],"major":[12],"noise":[13,23,66,96,104],"sources,":[14],"terms":[16],"of":[17,71,86,126,160,164,168,176,199],"distributions,":[18],"Gaussian":[20,35,93],"noise,":[21,59,94],"Poisson":[22,62,64,74,89,95],"and":[24,43,49,99,156,193],"impulse":[25,157],"noise.":[26,158],"Noise":[27],"acquired":[28],"by":[29,52,57],"images":[30,39,131],"during":[31],"transmission":[32,44],"would":[33],"be":[34,148],"distribution,":[37],"while":[38],"such":[40],"as":[41],"emission":[42],"tomography":[45],"images,":[46],"X-ray":[47],"films,":[48],"photographs":[50],"taken":[51],"satellites":[53],"usually":[55],"contaminated":[56],"quantum":[58],"which":[60],"is":[61,67,97,105,142,191],"distributed.":[63],"shot":[65],"a":[68,72,114,181,188],"natural":[69],"generalization":[70],"compound":[73],"process":[75],"when":[76],"the":[77,84,87,123,145,162,165,169,197],"summands":[78],"stochastic":[80],"processes":[81],"starting":[82],"at":[83],"points":[85],"underlying":[88],"process.":[90],"Unlike":[91],"additive":[92],"signal-dependent":[98],"consequently":[100],"separating":[101],"signal":[102,124,135],"from":[103],"more":[106],"difficult.":[107],"In":[108,138],"our":[109],"previous":[110],"papers":[111],"we":[112],"discussed":[113],"wavelet-based":[115],"maximum":[116,182],"likelihood":[117,183],"for":[118,180],"Bayesian":[119,166],"estimator":[120],"that":[121,144],"recovers":[122],"component":[125],"wavelet":[127],"coefficients":[128],"original":[130],"using":[132],"an":[133,174,186],"alpha-stable":[134],"prior":[136],"distribution.":[137],"this":[139,200],"paper,":[140],"it":[141],"demonstrated":[143],"method":[146],"can":[147],"extended":[149],"to":[150,195],"multi-noise":[151],"sources":[152],"comprising":[153],"Gaussian,":[154],"Poisson,":[155],"Results":[159],"varying":[161],"parameters":[163],"estimators":[167],"model":[170],"presented":[172,194],"after":[173],"investigation":[175],"/spl":[177],"alpha/-stable":[178],"simulations":[179],"estimator.":[184],"As":[185],"example,":[187],"colour":[189],"image":[190],"processed":[192],"illustrate":[196],"effectiveness":[198],"method.":[201]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
