Multivariate shrinkage functions for wavelet-based denoising

Levent Şendur, Ivan W. Selesnick

Research output: Contribution to journalConference articlepeer-review


The first nonlinear rules for wavelet based image denoising assume wavelet coefficients are independent. However it is well-known that there are strong dependencies between coefficients such as interscale and intrascale dependencies. We have introduced a non-Gaussian bivariate pdf which exploits the interscale dependencies between a coefficient and its parent [7, 8]. In this paper, how to extend this pdf in order to include the other dependencies will be discussed and in one example we will derive a multivariate shrinkage rule. The good performance of this new rule will be illustrated on an image denoising algorithm which capture also interscale dependencies.

Original languageEnglish (US)
Pages (from-to)953-957
Number of pages5
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
StatePublished - 2002
EventThe Thirty-Sixth Asilomar Conference on Signals Systems and Computers - Pacific Groove, CA, United States
Duration: Nov 3 2002Nov 6 2002

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications


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