Perona-Malik Model with Diffusion Coefficient Depending on Fractional Gradient via Caputo-Fabrizio Derivative

摘要: The Perona-Malik (PM) model is used successfully in image processing to eliminate noise while preserving edges; however, this has a major drawback: it tends make the look blocky. This work proposes modify PM by introducing Caputo-Fabrizio fractional gradient inside diffusivity function. Experiments with natural images show that our can suppress efficiently blocky effect. Also, good performance visual quality, high peak signal-to-noise ratio (PSNR), and lower value of mean absolute error (MAE) square (MSE).