Image denoising using wavelet embedded anisotropic diffusion (WEAD)

Abstract

In this paper a PDE based hybrid method for image denoising is introduced. The method is a bi-stage filter with anisotropic diffusion followed by wavelet based Bayesian shrinkage. Here efficient denoising is achieved by reducing the convergence time of anisotropic diffusion. As the convergence time decreases, image blurring can be restricted and produces a better denoised image than anisotropic or wavelet based methods. Experimental results based on PSNR, SSIM and edge analysis shows excellent performance of the proposed method.