On Anisotropic Variational Model for SAR Image Despeckling

Mostly motivated by practical applications especially in the field of satellite remote sensing of agricultural territories, we develop a novel approach to SAR image despeckling based on minimization of a special anisotropic energy functional. We propose a new statement of this problem in the weighted Sobolev spaces, provide a rigorous mathematical analysis of the proposed optimization problem, establish sufficient conditions of its solvability, show that the objective functional is Gateaux differentiable, and derive the corresponding optimality conditions. To illustrate the validity of the obtained results, we give some examples of numerical simulations with real satellite SAR images

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Publication Details

Journal
Journal of Optimization Differential Equations and their Applications
Published
2025-04-29
DOI
https://doi.org/10.15421/142505
Primary Topic
Image and Signal Denoising Methods
Type
article
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article

On Anisotropic Variational Model for SAR Image Despeckling

Peter I. Kogut, Natalya Ivanchuk
Journal of Optimization Differential Equations and their Applications
Image and Signal Denoising Methods
article

On Anisotropic Variational Model for SAR Image Despeckling

Peter I. Kogut, Natalya Ivanchuk
article en

Abstract

Mostly motivated by practical applications especially in the field of satellite remote sensing of agricultural territories, we develop a novel approach to SAR image despeckling based on minimization of a special anisotropic energy functional. We propose a new statement of this problem in the weighted Sobolev spaces, provide a rigorous mathematical analysis of the proposed optimization problem, establish sufficient conditions of its solvability, show that the objective functional is Gateaux differentiable, and derive the corresponding optimality conditions. To illustrate the validity of the obtained results, we give some examples of numerical simulations with real satellite SAR images

Journal of Optimization Differential Equations and their ApplicationsVol. 33(1)
National University of Water and Environmental Engineering (UA), Oles Honchar Dnipro National University (UA)
Openalex Percentile: Top 89%
Image and Signal Denoising Methods
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