{"id":"https://openalex.org/W1825404979","doi":"https://doi.org/10.1109/icpr.2002.1048291","title":"Improving de-noising by coefficient de-noising and dyadic wavelet transform","display_name":"Improving de-noising by coefficient de-noising and dyadic wavelet transform","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W1825404979","doi":"https://doi.org/10.1109/icpr.2002.1048291","mag":"1825404979"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2002.1048291","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2002.1048291","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Object recognition supported by user interaction for service robots","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/A5030709839","display_name":"Hailong Zhu","orcid":"https://orcid.org/0000-0001-9920-1379"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Hailong Zhu","raw_affiliation_strings":["Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong, P.R. China","[Department of Computer Science, Hong Kong University of Science and Technology, China]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong, P.R. China","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"[Department of Computer Science, Hong Kong University of Science and Technology, China]","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070273088","display_name":"James T. Kwok","orcid":"https://orcid.org/0000-0002-4828-8248"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"J.T. Kwok","raw_affiliation_strings":["Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong, P.R. China","[Department of Computer Science, Hong Kong University of Science and Technology, China]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong, P.R. China","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"[Department of Computer Science, Hong Kong University of Science and Technology, China]","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5030709839"],"corresponding_institution_ids":["https://openalex.org/I200769079"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.08556975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"273","last_page":"276"},"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":0.9948999881744385,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.785686194896698},{"id":"https://openalex.org/keywords/second-generation-wavelet-transform","display_name":"Second-generation wavelet transform","score":0.7371369004249573},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6783787608146667},{"id":"https://openalex.org/keywords/stationary-wavelet-transform","display_name":"Stationary wavelet transform","score":0.6576493978500366},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.6302565336227417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5477270483970642},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.5445634722709656},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.5321689248085022},{"id":"https://openalex.org/keywords/lifting-scheme","display_name":"Lifting scheme","score":0.5227822661399841},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5059904456138611},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47820210456848145},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.47089889645576477},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.46423545479774475},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43693453073501587},{"id":"https://openalex.org/keywords/harmonic-wavelet-transform","display_name":"Harmonic wavelet transform","score":0.4216564893722534},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3937421441078186},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18149414658546448},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.1716804802417755},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16618946194648743}],"concepts":[{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.785686194896698},{"id":"https://openalex.org/C111350171","wikidata":"https://www.wikidata.org/wiki/Q7443700","display_name":"Second-generation wavelet transform","level":5,"score":0.7371369004249573},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6783787608146667},{"id":"https://openalex.org/C73339587","wikidata":"https://www.wikidata.org/wiki/Q1375942","display_name":"Stationary wavelet transform","level":5,"score":0.6576493978500366},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.6302565336227417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5477270483970642},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.5445634722709656},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.5321689248085022},{"id":"https://openalex.org/C199550912","wikidata":"https://www.wikidata.org/wiki/Q3238415","display_name":"Lifting scheme","level":5,"score":0.5227822661399841},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5059904456138611},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47820210456848145},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.47089889645576477},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.46423545479774475},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43693453073501587},{"id":"https://openalex.org/C1109138","wikidata":"https://www.wikidata.org/wiki/Q3280930","display_name":"Harmonic wavelet transform","level":5,"score":0.4216564893722534},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3937421441078186},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18149414658546448},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.1716804802417755},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16618946194648743}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2002.1048291","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2002.1048291","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Object recognition supported by user interaction for service robots","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-38119","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-38119","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W59771946","https://openalex.org/W2004217976","https://openalex.org/W2115755118","https://openalex.org/W2115800795","https://openalex.org/W2120433189","https://openalex.org/W2146842127","https://openalex.org/W2151191108","https://openalex.org/W4214540058","https://openalex.org/W4214806317","https://openalex.org/W6921608856"],"related_works":["https://openalex.org/W1588899229","https://openalex.org/W1976022598","https://openalex.org/W2085792030","https://openalex.org/W2144408025","https://openalex.org/W1967182499","https://openalex.org/W2391053410","https://openalex.org/W1506615375","https://openalex.org/W2205192157","https://openalex.org/W2156522110","https://openalex.org/W4321517526"],"abstract_inverted_index":{"Soft":[0],"thresholding":[1],"has":[2],"been":[3],"a":[4,68],"standard":[5],"wavelet":[6,57,81,93],"de-noising":[7,43],"procedure":[8],"in":[9,22,54,96],"many":[10],"signal":[11],"and":[12,62],"image":[13],"processing":[14],"applications.":[15],"Theoretically":[16],"it":[17],"is":[18],"also":[19],"almost":[20],"optimal":[21],"the":[23,28,36,39,55,75,78,91,102,106,110,114],"sense":[24],"of":[25,41,77,90,109],"nearly":[26],"achieving":[27],"minimax":[29],"mean-squared":[30,70],"error.":[31],"Inspired":[32],"by":[33],"this":[34],"property,":[35],"paper":[37],"proposes":[38],"addition":[40],"coefficient":[42],"before":[44],"soft":[45],"thresholding.":[46],"This":[47],"extra":[48],"step":[49],"serves":[50],"to":[51,66],"reduce":[52],"noise":[53],"empirical":[56],"coefficients":[58],"at":[59],"each":[60],"scale,":[61],"can":[63],"be":[64],"shown":[65],"yield":[67],"lower":[69],"error":[71],"Moreover":[72,113],"we":[73],"advocate":[74],"use":[76],"translation-invariant":[79],"dyadic":[80],"transform,":[82],"together":[83],"with":[84,123],"an":[85],"approximate":[86],"self-dual":[87],"wavelet,":[88],"instead":[89],"discrete":[92],"transform":[94],"(DWT)":[95],"performing":[97],"denoising.":[98],"Experiments":[99],"show":[100],"that":[101],"proposed":[103],"method":[104],"improves":[105],"signal-to-noise":[107],"ratios":[108],"de-noised":[111,115],"signals.":[112],"signals":[116],"do":[117],"not":[118],"have":[119],"artifacts":[120],"typically":[121],"associated":[122],"DWT-based":[124],"methods.":[125]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
