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- Title
Tensor-guided learning for image denoising using anisotropic PDEs.
- Authors
Limami, Fakhr-eddine; Hadri, Aissam; Afraites, Lekbir; Laghrib, Amine
- Abstract
In this article, we introduce an advanced approach for enhanced image denoising using an improved space-variant anisotropic Partial Differential Equation (PDE) framework. Leveraging Weickert-type operators, this method relies on two critical parameters: λ and θ , defining local image geometry and smoothing strength. We propose an automatic parameter estimation technique rooted in PDE-constrained optimization, incorporating supplementary information from the original clean image. By combining these components, our approach achieves superior image denoising, pushing the boundaries of image enhancement methods. We employed a modified Alternating Direction Method of Multipliers (ADMM) procedure for numerical optimization, demonstrating its efficacy through thorough assessments and affirming its superior performance compared to alternative denoising methods.
- Publication
Machine Vision & Applications, 2024, Vol 35, Issue 3, p1
- ISSN
0932-8092
- Publication type
Article
- DOI
10.1007/s00138-024-01532-4