Method For Noises Removel Based On Pde

Among various kinds of image denoising methods, the Perona-Malik model is a representative Partial Differential Equation (PDE) based algorithm which effectively removes the noise as well as having edge enhancement simultaneously through anisotropic diffusion controlled by the diffusion coefficient. However, Partial Differential Equations (PDE) is good at removeling Gaussian noises, but it is not an ideal method to deal with salt-and-pepper noise. To realize less diffusion in the texture region and more smooth in flat region while implementing image denoising, this paper propose an improved PeronaMalik model based on new diffusion function which change with the number of iterations. The improved algorithm is applied on numerical simulation and practical images, and the quantitative analyzing results prove that the modified anisotropic diffusion model can preserve textures effectively while ruling out the noise, meanwhile, the PSNR are increased obviously.