Non-Lipschitz Variational Models and their Iteratively Reweighted Least Squares Algorithms for Image Denoising on Surfaces-Reference-Cited by-同舟云学术

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Non-Lipschitz Variational Models and their Iteratively Reweighted Least Squares Algorithms for Image Denoising on Surfaces

Published:2024-06-20 Issue:2 Volume:17 Page:1255-1283
ISSN:1936-4954
Container-title:SIAM Journal on Imaging Sciences
language:en
Short-container-title:SIAM J. Imaging Sci.

Author:

Liu Yuan¹,Wu Chunlin²^ORCID,Zeng Chao³

Affiliation:

1. School of Mathematics, Hefei University of Technology, Hefei, China.

2. School of Mathematical Sciences and LPMC, Nankai University, Tianjin, China.

3. Corresponding author. School of Mathematical Sciences and LPMC, Nankai University, Tianjin, China.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Tianjin City

Fundamental Research Funds for the Central Universities

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference38 articles.

1. Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Łojasiewicz Inequality

2. Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods

3. Anisotropic diffusion of surfaces and functions on surfaces

4. Segmentation and Restoration of Images on Surfaces by Parametric Active Contours with Topology Changes

5. Variational Problems and Partial Differential Equations on Implicit Surfaces

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