Fractional diffusion equation-based image denoising model using CN-GL scheme

In recent decades, variational methods have achieved great success in reducing noise owing to the use of total variation (TV). The TV-based denoising model introduced by Rudin-Osher-Fatemi (ROF) is playing vital role in denoising the different types of images. In this paper, a new denoising model based on space fractional diffusion equation is proposed with a finite domain discretized using effective applications of Crank-Nicholson and Grunwald Letnikov difference schemes. The ROF model has been adopted to solve the proposed model with the help of Alternative Direction Implicit method to denoise the image. The experimental results of the proposed model have been compared with those of the Gaussian model and it is observed that the Peak Signal-to-Noise Ratio has been improved.