<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Aiming at the problems of image edge blur and detail loss in most image denoising models, an image denoising model based on improved fractional calculus is proposed. Through the classification of image noise, the integer order PDE model is discussed. Based on the mathematical theory of fractional calculus, the fractional PDE model is discussed. The model is improved by combining texture detection operator, gray value detection operator, smoothing factor and fast algorithm. The simulation experiment of the model is carried out based on MATLAB simulation platform. The results show that the improved model is significantly better than other comparison models in image denoising effect, and the operation efficiency is higher.</p>
</abstract>

Aiming at the problems of image edge blur and detail loss in most image denoising models, an image denoising model based on improved fractional calculus is proposed. Through the classification of image noise, the integer order PDE model is discussed. Based on the mathematical theory of fractional calculus, the fractional PDE model is discussed. The model is improved by combining texture detection operator, gray value detection operator, smoothing factor and fast algorithm. The simulation experiment of the model is carried out based on MATLAB simulation platform. The results show that the improved model is significantly better than other comparison models in image denoising effect, and the operation efficiency is higher.

Image denoising model based on improved fractional calculus mathematical equation

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Aiming at the problems of image edge blur and detail loss in most image denoising models, an image denoising model based on improved fractional calculus is...

Image denoising model based on improved fractional calculus mathematical equation

Online veröffentlicht: 15. Juli 2022

Seitenbereich: 655 - 660

Eingereicht: 12. Feb. 2022

Akzeptiert: 11. Apr. 2022

DOI: https://doi.org/10.2478/amns.2022.2.0051

Schlüsselwörter
PDE, image denoising, fractional order, PSNR

© 2023 Kai Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1

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Image denoising model based on improved fractional calculus mathematical equation

Online veröffentlicht: 15. Juli 2022

Seitenbereich: 655 - 660

Eingereicht: 12. Feb. 2022

Akzeptiert: 11. Apr. 2022

DOI: https://doi.org/10.2478/amns.2022.2.0051

SchlüsselwörterPDE, image denoising, fractional order, PSNR

© 2023 Kai Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1

Figure 2

Figure 3

Schlüsselwörter
PDE, image denoising, fractional order, PSNR