Contourlet transform(CT) is a method of multiscale geometric analysis

which can result in a flexible multi resolution

local

and directional image expansion. But the Contourlet transform is not shift invariant

that will cause pseudo Gibbs phenomena around singularities in image denoising. In this paper we apply redundant contourlet transform with shift invariant to image denosing

which can capture the intrinsic geometrical structure of image. Meanwhile

we consider the dependencies between the coefficients and their parents in detail. We propose a method of image denoising based on redundant contourlet with bivariate shrinkage rules. The experimental results show that our method can obtain higher PSNR value and better visual effect compared with other methods.