Isotropic and anisotropic filtering techniques for image denoising: A comparative study with classification

Abstract

Denoising image is considered as a very important pretreatment and a basic operation for meaningful analysis of acquired image. In this paper, a comparative study of image denoising techniques is presented. We analyzed the ineffectiveness of isotropic and anisotropic diffusion and extended the work into the regular anisotropic diffusion. Isotropic diffusion is used at locations with low gradient and total variation based diffusion is used along likely edges. These denoising techniques have been applied to textured and satellite images to illustrate the methodology. The PSNR for the test data available is evaluated and the classification accuracy from these denoising techniques is validated. The experimental results demonstrate the superiority of the regular anisotropic diffusion for image denoining.