Convergent non-overlapping domain decomposition methods for variational image segmentation
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Publication:2014025
DOI10.1007/s10915-016-0207-8zbMath1409.68313OpenAlexW2339257204MaRDI QIDQ2014025
Yuping Duan, Xue-Cheng Tai, Huibin Chang
Publication date: 10 August 2017
Published in: Journal of Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10915-016-0207-8
Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Machine vision and scene understanding (68T45)
Related Items (9)
Fast non-overlapping domain decomposition methods for continuous multi-phase labeling problem ⋮ An overlapping domain decomposition framework without dual formulation for variational imaging problems ⋮ A Finite Element Approach for the Dual Rudin--Osher--Fatemi Model and Its Nonoverlapping Domain Decomposition Methods ⋮ An efficient multi-grid method for TV minimization problems ⋮ Non-Convex and Convex Coupling Image Segmentation via TGpV Regularization and Thresholding ⋮ A finite element nonoverlapping domain decomposition method with Lagrange multipliers for the dual total variation minimizations ⋮ RECENT ADVANCES IN DOMAIN DECOMPOSITION METHODS FOR TOTAL VARIATION MINIMIZATION ⋮ Overlapping Domain Decomposition Methods for Total Variation Denoising ⋮ Accelerated Non-Overlapping Domain Decomposition Method for Total Variation Minimization
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Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Nonlinear total variation based noise removal algorithms
- Global minimization for continuous multiphase partitioning problems using a dual approach
- Domain decomposition methods with graph cuts algorithms for total variation minimization
- Domain decomposition methods for nonlocal total variation image restoration
- A two-level domain decomposition method for image restoration
- A convergent overlapping domain decomposition method for total variation minimization
- Constraints on deformable models: Recovering 3D shape and nonrigid motion
- Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
- A geometric model for active contours in image processing
- Geodesic active contours
- An algorithm for total variation minimization and applications
- A multiphase level set framework for image segmentation using the Mumford and Shah model
- Rate of convergence for some constraint decomposition methods for nonlinear variational inequalities
- Completely convex formulation of the Chan-Vese image segmentation model
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Bregmanized domain decomposition for image restoration
- Domain decomposition methods in image denoising using Gaussian curvature
- Non-overlapping domain decomposition methods for dual total variation based image denoising
- Domain decomposition method for image deblurring
- Globally optimal geodesic active contours
- Block decomposition methods for total variation by primal-dual stitching
- Global and uniform convergence of subspace correction methods for some convex optimization problems
- Constrained Total Variation Deblurring Models and Fast Algorithms Based on Alternating Direction Method of Multipliers
- Subspace Correction Methods for a Class of Nonsmooth and Nonadditive Convex Variational Problems with Mixed $L^1/L^2$ Data-Fidelity in Image Processing
- Convergence Analysis of Primal-Dual Algorithms for a Saddle-Point Problem: From Contraction Perspective
- Optimal approximations by piecewise smooth functions and associated variational problems
- Subspace Correction Methods for Total Variation and $\ell_1$-Minimization
- Sequential and Parallel Splitting Methods for Bilinear Control Problems in Hilbert Spaces
- A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
- The Split Bregman Method for L1-Regularized Problems
- Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
- Augmented Lagrangian Method, Dual Methods, and Split Bregman Iteration for ROF, Vectorial TV, and High Order Models
- Handbook of Mathematical Methods in Imaging
- Rate of Convergence of Some Space Decomposition Methods for Linear and Nonlinear Problems
- Analysis of bounded variation penalty methods for ill-posed problems
- Active contours without edges
- Fast, robust total variation-based reconstruction of noisy, blurred images
- Explicit Algorithms for a New Time Dependent Model Based on Level Set Motion for Nonlinear Deblurring and Noise Removal
- Computational Methods for Inverse Problems
- Iterative Methods for Total Variation Denoising
- A Convex Approach to Minimal Partitions
- Convergence Rate of Overlapping Domain Decomposition Methods for the Rudin--Osher--Fatemi Model Based on a Dual Formulation
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