Optimization of parameters for image denoising algorithm pertaining to generalized Caputo-Fabrizio fractional operator

The aim of the present paper is to optimize the values of different parameters related to the image denoising algorithm involving Caputo Fabrizio fractional integral operator of non-singular type with the Mittag-Leffler function in generalized form. The algorithm aims to find the coefficients of a k...

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Bibliographic Details
Published inEURASIP journal on image and video processing Vol. 2024; no. 1; pp. 29 - 17
Main Authors Gaur, S., Khan, A. M., Suthar, D. L.
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 13.09.2024
Springer Nature B.V
SpringerOpen
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Summary:The aim of the present paper is to optimize the values of different parameters related to the image denoising algorithm involving Caputo Fabrizio 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 the noise from images. The optimization of kernel coefficients are done on the basis of 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 order. The novelty of the presented work lies in the development of a kernel utilizing coefficients from a fractional integral operator, specifically involving the Mittag-Leffler function in a more generalized form.
ISSN:1687-5281
1687-5176
1687-5281
DOI:10.1186/s13640-024-00632-5