O artykule
Data publikacji: 11 cze 2023
Zakres stron: 309 - 318
Otrzymano: 16 sty 2022
Przyjęty: 24 mar 2022
DOI: https://doi.org/10.2478/amns.2022.2.00020
Słowa kluczowe
© 2023 Junli Lei et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
The article first uses the fractional derivative to define a new fractional bounded variation function space. This method constructs the corresponding electronic information image model denoising mask by setting a smaller fractional integration order. The experimental results show that the image denoising algorithm based on fractional integration can not only improve the signal-to-noise ratio of the image compared with the traditional denoising method, but also can better retain the details of the edge and texture of the electronic information image.