JIP_V3_N3_RP2 S. Swarnalatha P. Satyanarayana Journal on Image Processing 2349-6827 3 3 11 16 Wavelet Transforms, Contourlet Transforms, Bi-variate Shrinkage, Translation Invariance, Gaussian Noise, Salt & Pepper Noise, Image Denoising Denoising refers to the recovery of an image that has been contaminated by noise due to poor quality of image acquisition and transmission. Accordingly, there is a need to reduce the noise present in the image as a consequence to produce the denoised image. This paper presents Image denoising using Wavelet transforms and Contourlet transforms governed by bivariate shrinkage (Bi-shrink) filter techniques. The Wavelet transforms have the shift sensitivity and poor directionality that is shown by peak signal-to-noise ratio. In this paper, Translation Invariant Contourlet Transforms is proposed to overcome the limitations of wavelet transforms, hence to increase the peak signal-to-noise ratio. The results illustrate the efficacy of the proposed transform in terms of peak signal-to-noise ratio, execution time and visual quality of images. July - September 2016 Copyright © 2016 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=8147