Abstract

A new method of image denoising using wavelet-based contourlet transform (WBCT) is proposed. Due to the lack of translation invariance of WBCT, image denoising by means of WBCT would lead to Gibbs-like phenomena. In the paper,cycle spinning-based technique is applied to develop translation invariant WBCT denoising scheme. Many simulation experiments with images contaminated by additive white Gaussian noise demonstrate that the performance of the proposed approach substantially surpasses that of previously wavelets methods using the cycle spinning both visually and in terms of the PSNR values, especially for the images that include mostly fine textures and contours.

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