Bregmanized domain decomposition for image restoration

DOI10.1007/s10915-012-9603-xzbMath1308.94020OpenAlexW2062653475MaRDI QIDQ1945371

Carola-Bibiane Schönlieb, Andreas Langer, Stanley J. Osher

Publication date: 8 April 2013

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-012-9603-x

zbMATH Keywords

total variationdomain decompositionimage restorationBregman distanceiterative Bregman algorithms

Mathematics Subject Classification ID

Numerical optimization and variational techniques (65K10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items

Block decomposition methods for total variation by primal-dual stitching, A novel piecewise multivariate function approximation method via universal matrix representation, Fast non-overlapping domain decomposition methods for continuous multi-phase labeling problem, Fast Nonoverlapping Block Jacobi Method for the Dual Rudin--Osher--Fatemi Model, Domain decomposition methods for nonlocal total variation image restoration, Convergent non-overlapping domain decomposition methods for variational image segmentation, Automated parameter selection for total variation minimization in image restoration, Non-overlapping domain decomposition methods for dual total variation based image denoising, A parallel line search subspace correction method for composite convex optimization, RECENT ADVANCES IN DOMAIN DECOMPOSITION METHODS FOR TOTAL VARIATION MINIMIZATION, Overlapping Domain Decomposition Methods for Total Variation Denoising, Convergence Rate of Overlapping Domain Decomposition Methods for the Rudin--Osher--Fatemi Model Based on a Dual Formulation, Accelerated Non-Overlapping Domain Decomposition Method for Total Variation Minimization

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• Smooth minimization of non-smooth functions
• Regularization of ill-posed linear equations by the non-stationary augmented Lagrangian method
• A convergent overlapping domain decomposition method for total variation minimization
• On total variation minimization and surface evolution using parametric maximum flows
• Iteratively solving linear inverse problems under general convex constraints
• Image recovery via total variation minimization and related problems
• An algorithm for total variation minimization and applications
• Subspace Correction Methods for Total Variation and $\ell_1$-Minimization
• The Split Bregman Method for L1-Regularized Problems
• Lagrange Multiplier Approach to Variational Problems and Applications
• Bregmanized Nonlocal Regularization for Deconvolution and Sparse Reconstruction
• On the performance of algorithms for the minimization of ℓ ₁ -penalized functionals
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Convergence of an Iterative Method for Total Variation Denoising
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Domain decomposition methods for linear inverse problems with sparsity constraints
• Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing
• An Infeasible Primal-Dual Algorithm for Total Bounded Variation--Based Inf-Convolution-Type Image Restoration
• Signal Recovery by Proximal Forward-Backward Splitting
• An Iterative Regularization Method for Total Variation-Based Image Restoration
• A study in the BV space of a denoising-deblurring variational problem
• Mathematical problems in image processing. Partial differential equations and the calculus of variations. Foreword by Olivier Faugeras