Abstract: An image denoising method based on the non-subsampled Shearlet domain Gaussi- an scale mixture model is presented.First,a Gaussian scale mixture model is used to model the correlation of the locally non-subsampled Shearlet coefficients of the noisy image.Then,the noise-free coefficients are estimated by the Bayes least square estimator.Finally,the inverse non-subsampled shearlet transform(NSST) is applied to these estimated Shearlet coefficients to obtain the denoised image.Experimental results show that the proposed method can remove Gaussian white noise while effectively preserving edges and texture information.At the same time,it can achieve a higher PSNR and mean structural similarity than the wavelet based GSM method,the curvelet domain multivariate shrinkage method and the non-subsampled Shearlet domain hard thresholding method.