Optimization of parameters for image denoising algorithm pertaining to Generalized Caputo-Febrizio Fractional Operator

Abstract

Abstract The aim of the present paper is to optimize the values of different parameters related to the image denoising algorithm involving Caputo Febrizio fractional integral operator of non-singular type with the Mittag-Leffler function in generalized form. The algorithm aims to find the coefficients of a kernel to remove out the noise from images. The optimization of kernel coefficients are done on the basis of the different numerical parameters like Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structure Similarity Index measure (SSIM) and Image Enhancement Factor (IEF). The performance of the proposed algorithm is investigated through above mentioned numeric parameters and visual perception with the other prevailed algorithms Experimental results demonstrate that the proposed optimized kernel based on generalized fractional operator performs favorably compared to state of the art methods. The uniqueness of the paper is to highlight the optimized values of performance parameters for different values of fractional orders. Mathematics subject classification: 345A08, 68U10, 94A08.