A dual-tree complex wavelet with application in image denoising

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dc.contributor.authorBaradarani, Aryaz
dc.contributor.authorYu, Runyi
dc.date.accessioned2026-02-06T17:54:40Z
dc.date.issued2007
dc.departmentDoğu Akdeniz Üniversitesi
dc.description2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007 --
dc.description.abstractThis paper introduces a recently designed dual-tree complex wavelet and studies its application in image denoising. The primal filter bank is selected to be the Daubechies 9/7 filter bank, and the dual filter bank is designed to have length of 10/8; both filter banks are biorthogonal and symmetric. The wavelets of the dual-tree filter bank form (almost) Hilbert transform pairs, allowing nearly shift-invariance and good directionality of the dual-tree complex wavelet transform. The transform is then used in image denoising. We employ the bivariate shrinkage algorithm for wavelet coefficient modeling and thresholding. Various images are tested. The experimental results compare favorably to some other dual-tree complex wavelets. © 2007 IEEE.
dc.identifier.doi10.1109/ICSPC.2007.4728541
dc.identifier.endpage1206
dc.identifier.isbn9781424412365
dc.identifier.scopus2-s2.0-46649094703
dc.identifier.scopusqualityN/A
dc.identifier.startpage1203
dc.identifier.urihttps://doi.org/10.1109/ICSPC.2007.4728541
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/
dc.identifier.urihttps://hdl.handle.net/11129/7536
dc.indekslendigikaynakScopus
dc.language.isoen
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260204
dc.subjectBivariate shrinkage
dc.subjectDual-tree complex wavelets
dc.subjectImage denoising
dc.subjectWavelet transforms
dc.titleA dual-tree complex wavelet with application in image denoising
dc.typeConference Object

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