, 3(3), 11-16.'>
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.