Adaptive denoising based on lifting scheme

Yonghong Wu, Quan Pan, Hongcai Zhang, Shaowu Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Observing that the Haar wavelet is sensitive to step edges, and the CDF(2,2) wavelet which is a subset of the Cohen-Daubechies-Feauveau family performs well for smooth signals, we present a new adaptive wavelet transform via the lifting scheme for noise reduction. Unlike many popular wavelets that adapt scale-by-scale, the proposed wavelet can adapt point-by-point. Experiment results show that the proposed method has advantages of both the Haar and CDF(2,2) wavelets and performs well for the smooth and edge-dominated regions. Moreover, the interval of the switch thresholding parameter of the proposed wavelet is given by experiments.

Original languageEnglish
Title of host publication2004 7th International Conference on Signal Processing Proceedings, ICSP
Pages350-353
Number of pages4
StatePublished - 2004
Event2004 7th International Conference on Signal Processing Proceedings, ICSP - Beijing, China
Duration: 31 Aug 20044 Sep 2004

Publication series

Name2004 7th International Conference on Signal Processing Proceedings, ICSP

Conference

Conference2004 7th International Conference on Signal Processing Proceedings, ICSP
Country/TerritoryChina
CityBeijing
Period31/08/044/09/04

Keywords

  • Adaptive wavelet transform
  • Lifting scheme
  • Switch thresholding parameter

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