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A new method for image denoising based on the contourlet transform, which has been recently introduced is presented in this paper. Image denoising by means of the contourlet transform introduces many visual artifacts due to the Gibbs-Iike phenomena. Due to the lack of translation invariance of the contourlet transform, we employ a cycle-spinning-based technique to develop translation invariant contourlet denoising scheme. This scheme achieves enhanced estimation results for images that are corrupted with additive Gaussian noise over a wide range of noise variance. Our experiments show that the proposed approach outperforms the translation invariant wavelets both visually and in terms of the PSNR values, especially for the images that include mostly fine textures and contours.