{"id":"https://openalex.org/W2054360077","doi":"https://doi.org/10.1109/icassp.2002.5744031","title":"A bivariate shrinkage function for wavelet-based denoising","display_name":"A bivariate shrinkage function for wavelet-based denoising","publication_year":2002,"publication_date":"2002-05-01","ids":{"openalex":"https://openalex.org/W2054360077","doi":"https://doi.org/10.1109/icassp.2002.5744031","mag":"2054360077"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2002.5744031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2002.5744031","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Conference on Acoustics Speech and Signal Processing","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/A5051775377","display_name":"L. Sendur","orcid":null},"institutions":[{"id":"https://openalex.org/I90965887","display_name":"SUNY Polytechnic Institute","ror":"https://ror.org/000fxgx19","country_code":"US","type":"education","lineage":["https://openalex.org/I90965887"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Levent Sendur","raw_affiliation_strings":["Electrical Engineering, Polytechnic University, Brooklyn, NY, USA","Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201, USA"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Polytechnic University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I90965887"]},{"raw_affiliation_string":"Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201, USA","institution_ids":["https://openalex.org/I90965887"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058321875","display_name":"Ivan Selesnick","orcid":"https://orcid.org/0000-0002-4939-3971"},"institutions":[{"id":"https://openalex.org/I90965887","display_name":"SUNY Polytechnic Institute","ror":"https://ror.org/000fxgx19","country_code":"US","type":"education","lineage":["https://openalex.org/I90965887"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ivan W. Selesnick","raw_affiliation_strings":["Electrical Engineering, Polytechnic University, Brooklyn, NY, USA","Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201, USA"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Polytechnic University, Brooklyn, NY, USA","institution_ids":["https://openalex.org/I90965887"]},{"raw_affiliation_string":"Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201, USA","institution_ids":["https://openalex.org/I90965887"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051775377"],"corresponding_institution_ids":["https://openalex.org/I90965887"],"apc_list":null,"apc_paid":null,"fwci":2.24,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.86463415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"II","last_page":"1261"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9883000254631042,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.864867091178894},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.5900691151618958},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5814903974533081},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5670946836471558},{"id":"https://openalex.org/keywords/cascade-algorithm","display_name":"Cascade algorithm","score":0.5552051663398743},{"id":"https://openalex.org/keywords/shrinkage","display_name":"Shrinkage","score":0.4908464550971985},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.48919227719306946},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4633501172065735},{"id":"https://openalex.org/keywords/shrinkage-estimator","display_name":"Shrinkage estimator","score":0.4358222484588623},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.42883551120758057},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.42433464527130127},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.41344940662384033},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.412415087223053},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3934621810913086},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.38348841667175293},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34080374240875244},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.17022600769996643},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07084491848945618},{"id":"https://openalex.org/keywords/bias-of-an-estimator","display_name":"Bias of an estimator","score":0.06293770670890808}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.864867091178894},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.5900691151618958},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5814903974533081},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5670946836471558},{"id":"https://openalex.org/C88829872","wikidata":"https://www.wikidata.org/wiki/Q5048176","display_name":"Cascade algorithm","level":5,"score":0.5552051663398743},{"id":"https://openalex.org/C180145272","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage","level":2,"score":0.4908464550971985},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.48919227719306946},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4633501172065735},{"id":"https://openalex.org/C102592046","wikidata":"https://www.wikidata.org/wiki/Q7504144","display_name":"Shrinkage estimator","level":5,"score":0.4358222484588623},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.42883551120758057},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.42433464527130127},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.41344940662384033},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.412415087223053},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3934621810913086},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.38348841667175293},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34080374240875244},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.17022600769996643},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07084491848945618},{"id":"https://openalex.org/C191393472","wikidata":"https://www.wikidata.org/wiki/Q15222032","display_name":"Bias of an estimator","level":4,"score":0.06293770670890808},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C165646398","wikidata":"https://www.wikidata.org/wiki/Q3755281","display_name":"Minimum-variance unbiased estimator","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2002.5744031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2002.5744031","pdf_url":null,"source":{"id":"https://openalex.org/S4363607879","display_name":"IEEE International Conference on Acoustics Speech and Signal Processing","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE International Conference on Acoustics Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1775729916","https://openalex.org/W2057612871","https://openalex.org/W2082076175","https://openalex.org/W2098821691","https://openalex.org/W2104872117","https://openalex.org/W2119938170","https://openalex.org/W2126683262","https://openalex.org/W2134929491","https://openalex.org/W2143304716","https://openalex.org/W2143421693","https://openalex.org/W2146842127","https://openalex.org/W2156706175","https://openalex.org/W2163612361","https://openalex.org/W2498840900","https://openalex.org/W4240337472","https://openalex.org/W4295332281","https://openalex.org/W6674704741","https://openalex.org/W6677760137"],"related_works":["https://openalex.org/W2380372197","https://openalex.org/W2053682625","https://openalex.org/W2085792030","https://openalex.org/W68308810","https://openalex.org/W2358271565","https://openalex.org/W3145681365","https://openalex.org/W2106763914","https://openalex.org/W2351270432","https://openalex.org/W1977389157","https://openalex.org/W2373036300"],"abstract_inverted_index":{"Most":[0],"simple":[1,42],"nonlinear":[2,43],"thresholding":[3],"rules":[4],"for":[5],"wavelet-based":[6],"denoising":[7],"assume":[8,63],"the":[9,35,51,64],"wavelet":[10,15,38,67],"coefficients":[11,16],"are":[12],"independent.":[13],"However,":[14],"of":[17,37,66],"natural":[18],"images":[19],"have":[20],"significant":[21],"dependency.":[22],"In":[23],"this":[24],"paper,":[25],"a":[26,41],"new":[27,58],"heavy-tailed":[28],"bivariate":[29],"pdf":[30,52],"is":[31,48],"proposed":[32],"to":[33],"model":[34],"statistics":[36],"coefficients,":[39],"and":[40],"threshold":[44],"function":[45,60],"(shrinkage":[46],"function)":[47],"derived":[49],"from":[50],"using":[53],"Bayesian":[54],"estimation":[55],"theory.":[56],"The":[57],"shrinkage":[59],"does":[61],"not":[62],"independence":[65],"coefficients.":[68]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
