A novel coupled <i>p</i> ( <i>x</i> ) and fractional PDE denoising model with theoretical results

In this paper, we formulate a new coupled PDE-based configuration for image denoising. We elaborate a new class of coupled PDE that involves a p(x)-Laplace and a controlled fractional-type operator, which takes into account the texture and smooth components during the recovering process. We give some essential theoretical results and we establish the well-posedness of the suggested coupled equation based on Galerkin approximation. Finally, we perform a fully discretization part of the system and illustrate some various numerical realizations to ensure the efficiency of our coupled PDE by conducting some comparison experiments against state of art PDE denoising models.

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Publication Details

Journal
International Journal of Computer Mathematics
Published
2024-08-26
DOI
https://doi.org/10.1080/00207160.2024.2394860
Citations
6
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
1.50
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article

A novel coupled p ( x ) and fractional PDE denoising model with theoretical results

Amine Laghrib, Abdelmajid El Hakoume, Lekbir Afraites, Ziad Zaabouli
6 citations
International Journal of Computer Mathematics
Image and Signal Denoising Methods
1.50
article

A novel coupled p ( x ) and fractional PDE denoising model with theoretical results

Amine Laghrib, Abdelmajid El Hakoume, Lekbir Afraites, Ziad Zaabouli
article en
6 citations

Abstract

In this paper, we formulate a new coupled PDE-based configuration for image denoising. We elaborate a new class of coupled PDE that involves a p(x)-Laplace and a controlled fractional-type operator, which takes into account the texture and smooth components during the recovering process. We give some essential theoretical results and we establish the well-posedness of the suggested coupled equation based on Galerkin approximation. Finally, we perform a fully discretization part of the system and illustrate some various numerical realizations to ensure the efficiency of our coupled PDE by conducting some comparison experiments against state of art PDE denoising models.

International Journal of Computer MathematicsVol. 101(11)
Abdelmalek Essaâdi University (MA), Université Sultan Moulay Slimane (MA)
Openalex Percentile: Top 16%
Image and Signal Denoising Methods
1.50
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