An augmented Lagrangian method for \(\mathrm{TV}_g +L^1\)-norm minimization
type: Item
instance of: scholarly article
title: An augmented Lagrangian method for \(\mathrm{TV}_g +L^1\)-norm minimization
zbMATH Open document ID: 1255.94019
author: Jonas Koko
author: Stéphanie Jehan-Besson
published in: Journal of Mathematical Imaging and Vision
publication date: 2013-01-22T00:00:00Z
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 49N45
zbMATH DE Number: 6127941
zbMATH Keywords: total variation
zbMATH Keywords: \(L^1\)-norm
zbMATH Keywords: augmented Lagrangian
zbMATH Keywords: Fenchel duality
zbMATH Keywords: Uzawa methods
zbMATH Keywords: salt and pepper noise removal
zbMATH Keywords: shape retrieval
zbMATH Keywords: geometric filtering
MaRDI profile type: Publication
full work available at URL: s10851-010-0219-1
OpenAlex ID: W2241097341
cites work: Digital filters as absolute norm regularizers
cites work: Dual norms and image decomposition models
cites work: Structure-texture image decomposition -- modeling, algorithms, and parameter selection
cites work: Scale Space and PDE Methods in Computer Vision
cites work: Q3690580
cites work: Two-phase approach for deblurring images corrupted by impulse plus Gaussian noise
cites work: A geometric model for active contours in image processing
cites work: Geodesic active contours
cites work: An algorithm for total variation minimization and applications
cites work: A Nonlinear Primal-Dual Method for Total Variation-Based Image Restoration
cites work: Aspects of Total Variation RegularizedL1Function Approximation
cites work: Active contours without edges
cites work: Space variant median filters for the restoration of impulse noise corrupted images
cites work: Image restoration with discrete constrained total variation. I: Fast and exact optimization
cites work: Image restoration with discrete constrained total variation. II: Levelable functions, convex priors and non-convex cases
cites work: The TVL1 Model: A Geometric Point of View
cites work: Noise adaptive soft-switching median filter
cites work: An integral formula for total gradient variation
cites work: Q3038523
cites work: Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration
cites work: Q3995612
cites work: Constraints on deformable models: Recovering 3D shape and nonrigid motion
cites work: Uzawa block relaxation domain decomposition method for the two-body contact problem with Tresca friction
cites work: Q4435806
cites work: Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers
cites work: A variational approach to remove outliers and impulse noise
cites work: Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
cites work: Geometric Level Set Methods in Imaging, Vision, and Graphics
cites work: Nonlinear total variation based noise removal algorithms
cites work: Q4256621
cites work: Efficient Schemes for Total Variation Minimization Under Constraints in Image Processing
cites work: The Total Variation Regularized $L^1$ Model for Multiscale Decomposition
DOI: 10.1007/S10851-010-0219-1
Recommended article: An efficient augmented Lagrangian method with applications to total variation minimization
Recommended article: An Augmented Lagrangian Method for $\ell_{1}$-Regularized Optimization Problems with Orthogonality Constraints
Recommended article: An Augmented Lagrangian Method for Non-Lipschitz Nonconvex Programming
Recommended article: Augmented Lagrangian methods for convex matrix optimization problems
Recommended article: Augmented Lagrangian methods for nonsmooth, convex optimization in Hilbert spaces
Recommended article: Augmented Lagrangian methods for variational inequality problems
Recommended article: Accelerated augmented Lagrangian method for total variation minimization
Recommended article: Q5058515
Recommended article: Linearized augmented Lagrangian and alternating direction methods for nuclear norm minimization
Recommended article: On the convergence of augmented Lagrangian methods for nonlinear semidefinite programming
description: scientific article; zbMATH DE number 6127941