The requirement for image improvement and restoration is experienced in numerous down to earth applications. For example, mutilation because of Gaussian noise can be caused by low quality image obtaining, images saw in a noisy situation or noise intrinsic in correspondence channels. In this proposition, image denoising is examined. In the wake of looking into standard image denoising strategies as connected in the spatial, frequency and wavelet domains of the noisy image, the proposal sets out on the undertaking of creating and exploring different avenues regarding new image denoising techniques in view of wiener channel and Bayesian shrinkage govern utilizing wavelet change. Specifically, four new image denoising strategies are proposed. The performance of the denoising results is assessed using PSNR, SSIM and UIQI. It is observed that the proposed model 1 out of four models shows the best results in terms of quantitative and qualitative analysis.