Augmented Lagrangian method for total variation based image restoration and segmentation over triangulated surfaces

DOI10.1007/s10915-011-9477-3zbMath1253.94017OpenAlexW2077970616MaRDI QIDQ421313

Xue-Cheng Tai, Juyong Zhang, Yuping Duan, Chunlin Wu

Publication date: 23 May 2012

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

Full work available at URL: https://doi.org/10.1007/s10915-011-9477-3

zbMATH Keywords

total variationoperator splittingimage segmentationaugmented Lagrangian methodimage restorationtriangulated surfaces

Mathematics Subject Classification ID

Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (14)

Implicit surface reconstruction with total variation regularization ⋮ Segmentation and restoration of images on surfaces by parametric active contours with topology changes ⋮ A splitting algorithm for image segmentation on manifolds represented by the grid based particle method ⋮ Inexact first-order primal-dual algorithms ⋮ Discrete total variation with finite elements and applications to imaging ⋮ Total generalized variation for triangulated surface data ⋮ Total Generalized Variation for Piecewise Constant Functions on Triangular Meshes with Applications in Imaging ⋮ Convex non-convex segmentation of scalar fields over arbitrary triangulated surfaces ⋮ A Mean Curvature Regularized Based Model for Demodulating Phase Maps from Fringe Patterns ⋮ TGV-based multiplicative noise removal approach: models and algorithms ⋮ A novel anisotropic second order regularization for mesh denoising ⋮ A wavelet frame approach for removal of mixed Gaussian and impulse noise on surfaces ⋮ Total generalized variation restoration with non-quadratic fidelity ⋮ A Novel Mesh Denoising Method Based on Relaxed Second-Order Total Generalized Variation

Uses Software

• RecPF

Cites Work

• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• Global minimization for continuous multiphase partitioning problems using a dual approach
• Augmented Lagrangian method for total variation restoration with non-quadratic fidelity
• Geometric applications of the split Bregman method: segmentation and surface reconstruction
• A unified primal-dual algorithm framework based on Bregman iteration
• A finite algorithm for finding the projection of a point onto the canonical simplex of \({\mathbb R}^ n\)
• Constraints on deformable models: Recovering 3D shape and nonrigid motion
• 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
• Diffusion snakes: Introducing statistical shape knowledge into the Mumford-Shah functional
• Level set methods and dynamic implicit surfaces
• Completely convex formulation of the Chan-Vese image segmentation model
• Fast dual minimization of the vectorial total variation norm and applications to color image processing
• Optimal approximations by piecewise smooth functions and associated variational problems
• Global Solutions of Variational Models with Convex Regularization
• A Fast Total Variation Minimization Method for Image Restoration
• A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
• The Split Bregman Method for L1-Regularized Problems
• A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration
• Scale-Space Analysis of Discrete Filtering over Arbitrary Triangulated Surfaces
• Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
• An EM algorithm for wavelet-based image restoration
• A binary level set model and some applications to Mumford-Shah image segmentation
• Efficient Schemes for Total Variation Minimization Under Constraints in Image Processing
• Augmented Lagrangian Method, Dual Methods, and Split Bregman Iteration for ROF, Vectorial TV, and High Order Models
• Augmented Lagrangian Method, Dual Methods and Split Bregman Iteration for ROF Model
• A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
• Active contours without edges
• Wavelet Algorithms for High-Resolution Image Reconstruction
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• An Iterative Shrinkage Approach to Total-Variation Image Restoration
• Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing
• A variant of the level set method and applications to image segmentation

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