A novel fractional mask for image denoising based on fractal–fractional integral

Abstract

The paper introduced an image-denoising algorithm based on the fractal–fractional integral operator for removing Gaussian noise in images. Using this algorithm fractional masks have been constructed. The capacity of the fractal–fractional integral mask to smooth the Gaussian noisy images for varied noise levels has been demonstrated through experiments. Peak signal-to-noise ratio (PSNR) is used for denoising images to analyse performance. The acquired experimental results demonstrate that fractal–fractional masks have comparable capabilities to some recently developed masks and are computationally efficient.