Dual-Primal Domain Decomposition Methods for the Total Variation Minimization
DOI10.1007/978-3-319-52389-7_38zbMath1367.65031OpenAlexW2597277594MaRDI QIDQ5282931
Publication date: 17 July 2017
Published in: Lecture Notes in Computational Science and Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-52389-7_38
Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Parallel numerical computation (65Y05)
Cites Work
- Nonlinear total variation based noise removal algorithms
- A two-level domain decomposition method for image restoration
- A convergent overlapping domain decomposition method for total variation minimization
- An algorithm for total variation minimization and applications
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Non-overlapping domain decomposition methods for dual total variation based image denoising
- Block decomposition methods for total variation by primal-dual stitching
- Subspace Correction Methods for Total Variation and $\ell_1$-Minimization
- Convergence Rate of Overlapping Domain Decomposition Methods for the Rudin--Osher--Fatemi Model Based on a Dual Formulation
- Domain decomposition methods for linear inverse problems with sparsity constraints
- Convergence of a block coordinate descent method for nondifferentiable minimization
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