An efficient anisotropic diffusion model for image denoising with edge preservation

Abstract Anisotropic diffusion filtering is a widely used partial differential equation (PDE) based technique, which works effectively for removal of noise and preserving edges. This technique is highly dependent on diffusion coefficient and threshold parameter. In this work, we propose a new diffusion coefficient and image dependent threshold parameter which has a faster rate of convergence than those found in literature. The new technique outperforms the traditional models of anisotropic diffusion. Experimental results show the superiority of the proposed work over traditional anisotropic diffusion models.