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Publicado en línea: 11 jun 2023
Páginas: 309 - 318
Recibido: 16 ene 2022
Aceptado: 24 mar 2022
DOI: https://doi.org/10.2478/amns.2022.2.00020
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© 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.