{"id":"https://openalex.org/W7124420837","doi":"https://doi.org/10.1142/s0219691326500025","title":"Adaptive bivariate wavelet shrinkage for image denoising with spatially varying noise","display_name":"Adaptive bivariate wavelet shrinkage for image denoising with spatially varying noise","publication_year":2026,"publication_date":"2026-01-16","ids":{"openalex":"https://openalex.org/W7124420837","doi":"https://doi.org/10.1142/s0219691326500025"},"language":"en","primary_location":{"id":"doi:10.1142/s0219691326500025","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691326500025","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-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/A5022874184","display_name":"Guang Yi Chen","orcid":"https://orcid.org/0000-0002-4811-2402"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Guang Yi Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4811-2402","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123190737","display_name":"M. Omair Ahmad","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. Omair Ahmad","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada"],"raw_orcid":"https://orcid.org/0000-0002-2924-6659","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123238349","display_name":"M. N. S. Swamy","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"M. N. S. Swamy","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada"],"raw_orcid":"https://orcid.org/0000-0002-3989-5476","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06174434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":"02","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9702000021934509,"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":0.9702000021934509,"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":0.00430000014603138,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.0027000000700354576,"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/noise","display_name":"Noise (video)","score":0.7670000195503235},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.7002999782562256},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6837999820709229},{"id":"https://openalex.org/keywords/value-noise","display_name":"Value noise","score":0.5823000073432922},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.5679000020027161},{"id":"https://openalex.org/keywords/shrinkage","display_name":"Shrinkage","score":0.555400013923645},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.5325999855995178},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5049999952316284},{"id":"https://openalex.org/keywords/gradient-noise","display_name":"Gradient noise","score":0.46000000834465027}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7670000195503235},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.7002999782562256},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6837999820709229},{"id":"https://openalex.org/C182163834","wikidata":"https://www.wikidata.org/wiki/Q2926529","display_name":"Value noise","level":5,"score":0.5823000073432922},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.5679000020027161},{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.555400013923645},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.5325999855995178},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5049999952316284},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5005999803543091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47780001163482666},{"id":"https://openalex.org/C200378446","wikidata":"https://www.wikidata.org/wiki/Q4147391","display_name":"Gradient noise","level":5,"score":0.46000000834465027},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4571000039577484},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.45590001344680786},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44130000472068787},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.42419999837875366},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.3781999945640564},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.36570000648498535},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35899999737739563},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.34119999408721924},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.3068000078201294},{"id":"https://openalex.org/C293773","wikidata":"https://www.wikidata.org/wiki/Q7608015","display_name":"Step detection","level":3,"score":0.2897000014781952},{"id":"https://openalex.org/C102592046","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage estimator","level":5,"score":0.2596000134944916},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C101453961","wikidata":"https://www.wikidata.org/wiki/Q7048948","display_name":"Non-local means","level":4,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219691326500025","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691326500025","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W339356811","https://openalex.org/W1899329334","https://openalex.org/W1984487106","https://openalex.org/W2055750192","https://openalex.org/W2056370875","https://openalex.org/W2097073572","https://openalex.org/W2129276048","https://openalex.org/W2140742952","https://openalex.org/W2146842127","https://openalex.org/W2152047336","https://openalex.org/W2158940042","https://openalex.org/W2406034201","https://openalex.org/W2508457857","https://openalex.org/W2769290426","https://openalex.org/W2800744053","https://openalex.org/W2809980976","https://openalex.org/W2899191282","https://openalex.org/W2910259740","https://openalex.org/W2916190813","https://openalex.org/W3080848135","https://openalex.org/W3195176541","https://openalex.org/W4285128412","https://openalex.org/W4313038057","https://openalex.org/W4386590825","https://openalex.org/W4390204279","https://openalex.org/W4392590783"],"related_works":[],"abstract_inverted_index":{"Image":[0],"denoising":[1],"is":[2,18,80],"a":[3,52,63],"very":[4,81],"important":[5],"topic":[6],"in":[7,32,98],"many":[8],"real-life":[9,99],"applications.":[10],"In":[11,34],"most":[12],"existing":[13],"works,":[14],"the":[15,24,39,58,103],"noise":[16,54,59,74,93,114,117],"level":[17],"assumed":[19],"to":[20,44],"be":[21,30],"constant":[22,53],"over":[23],"whole":[25],"image.":[26],"Nevertheless,":[27],"this":[28,35],"can":[29,69,88,96],"violated":[31],"practice.":[33],"paper,":[36],"we":[37,56,68],"improve":[38],"bivariate":[40],"wavelet":[41],"shrinkage":[42],"(BivShrink)":[43],"deal":[45,70,89],"with":[46,71,90],"spatially":[47,72,91,112],"varying":[48,73,92,113],"noise.":[49],"Instead":[50],"of":[51,105],"level,":[55],"estimate":[57],"levels":[60],"locally":[61],"within":[62],"small":[64],"neighborhood":[65],"so":[66],"that":[67],"more":[75],"effectively.":[76],"Our":[77],"new":[78,107],"method":[79,108],"fast":[82],"for":[83,109],"image":[84],"denoising,":[85],"and":[86,115],"it":[87],"levels,":[94],"which":[95],"happen":[97],"images.":[100,120],"Experiments":[101],"demonstrate":[102],"success":[104],"our":[106],"reducing":[110],"both":[111],"uniform":[116],"from":[118],"noisy":[119]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-01-17T00:00:00"}