A signal denoising algorithm based on overcomplete wavelet representations and Gaussian models

  • Authors:

  • Guang Deng;David B. H. Tay;Slaven Marusic

  • Affiliations:

  • Department of Electronic Engineering, La Trobe University, Vic. 3083, Australia;Department of Electronic Engineering, La Trobe University, Vic. 3083, Australia;School of Electrical Engineering and Telecommunications, The University of New South Wales, Australia

  • Venue:
  • Signal Processing
  • Year:
  • 2007

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Abstract

In this paper, we propose a simple signal estimation algorithm based on multiple wavelet representations and Gaussian observation models. The proposed algorithm has two major steps: a joint-optimum estimation of the wavelet coefficients and an averaging of the denoised images. Experimental results show that the denoising performance of proposed algorithm is comparable to that of the state of the art.