A new application of fractional Atangana–Baleanu derivatives: Designing ABC-fractional masks in image processing

Based on a new definition for derivative and integral of fractional-order, several fractional masks have been presented for the use of image denoising. In each method, the process involves constructing a square and then applying it to all the corresponding blocks in the noisy image. We have measured the denoising performance of our proposed masks by employing some known indexes. They are the peak signal-to-noise ratio (PSNR), ENTROPY, and SSIM. The obtained experimental results show that our proposed masks are computationally efficient, and their performances are compatible with other standard and fractional smoothing filters.