Well-posedness of a variable-exponent telegraph equation applied to image despeckling

In this paper, we present a telegraph diffusion model with variable exponents for image despeckling. Moving beyond the traditional assumption of a constant exponent in the telegraph diffusion framework, we explore three distinct variable exponents for edge detection. All of these depend on the gray level of the image or its gradient. We rigorously prove the existence and uniqueness of weak solutions of our model in a functional setting and perform numerical experiments to assess how well it can despeckle noisy gray-level images. We consider both a range of natural images contaminated by varying degrees of artificial speckle noise and synthetic aperture radar (SAR) images. We finally compare our method with the nonlocal speckle removal technique and find that our model outperforms the latter at speckle elimination and edge preservation.

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Publication Details

Journal
Evolution equations and control theory
Published
2025-01-01
DOI
https://doi.org/10.3934/eect.2025039
Primary Topic
Image and Signal Denoising Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Well-posedness of a variable-exponent telegraph equation applied to image despeckling

Sudeb Majee, Åke Brännström, Niklas L. P. Lundström
Evolution equations and control theory
Image and Signal Denoising Methods
article

Well-posedness of a variable-exponent telegraph equation applied to image despeckling

Sudeb Majee, Åke Brännström, Niklas L. P. Lundström
article en

Abstract

In this paper, we present a telegraph diffusion model with variable exponents for image despeckling. Moving beyond the traditional assumption of a constant exponent in the telegraph diffusion framework, we explore three distinct variable exponents for edge detection. All of these depend on the gray level of the image or its gradient. We rigorously prove the existence and uniqueness of weak solutions of our model in a functional setting and perform numerical experiments to assess how well it can despeckle noisy gray-level images. We consider both a range of natural images contaminated by varying degrees of artificial speckle noise and synthetic aperture radar (SAR) images. We finally compare our method with the nonlocal speckle removal technique and find that our model outperforms the latter at speckle elimination and edge preservation.

Evolution equations and control theoryVol. 14(6)
Statistics Sweden (SE), Umeå University (SE)
Kempe Foundation, Kempestiftelserna
Openalex Percentile: Top 91%
Image and Signal Denoising Methods
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Well-posedness of a variable-exponent telegraph equation applied to image despeckling — Sudeb Majee, Åke Brännström, et al. · Evolution equations and control theory (2025) | TGRS Research Map | TGRS