Block-based refitting in \(\ell_{12}\) sparse regularization

DOI10.1007/s10851-020-00993-2OpenAlexW3129800025MaRDI QIDQ2031749

Nicolas Papadakis, Samuel Vaiter, Charles-Alban Deledalle, Joseph Salmon

Publication date: 14 June 2021

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.11186

zbMATH Keywords

total variationbias correctionrefittingblock sparsity

Mathematics Subject Classification ID

Computer science (68-XX) Information and communication theory, circuits (94-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonlinear total variation based noise removal algorithms
• Image restoration using total variation with overlapping group sparsity
• Exponential screening and optimal rates of sparse estimation
• Component selection and smoothing in multivariate nonparametric regression
• Bias reduction in variational regularization
• The cosparse analysis model and algorithms
• Least angle regression. (With discussion)
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Least squares after model selection in high-dimensional sparse models
• Directional total generalized variation regularization
• Contrast invariant SNR and isotonic regressions
• Crouzeix-Raviart approximation of the total variation on simplicial meshes
• Local behavior of sparse analysis regularization: applications to risk estimation
• Sparsity of solutions for variational inverse problems with finite-dimensional data
• On Lasso refitting strategies
• The degrees of freedom of partly smooth regularizers
• Optimization with Sparsity-Inducing Penalties
• Robust Sparse Analysis Regularization
• Discrete Total Variation: New Definition and Minimization
• Spectral Decompositions Using One-Homogeneous Functionals
• Boosting of Image Denoising Algorithms
• On the Numerical Solution of Heat Conduction Problems in Two and Three Space Variables
• On Debiasing Restoration Algorithms: Applications to Total-Variation and Nonlocal-Means
• Splitting Algorithms for the Sum of Two Nonlinear Operators
• Edge-preserving and scale-dependent properties of total variation regularization
• Boosting With theL₂Loss
• High-Order Total Variation-Based Image Restoration
• Model Consistency of Partly Smooth Regularizers
• Audio Denoising by Time-Frequency Block Thresholding
• Convergence rates and structure of solutions of inverse problems with imperfect forward models
• Decomposition of images by the anisotropic Rudin-Osher-Fatemi model
• A Multiscale Image Representation Using Hierarchical (BV,L²) Decompositions
• Recovery of Blocky Images from Noisy and Blurred Data
• A Total Variation Spectral Framework for Scale and Texture Analysis
• On Representer Theorems and Convex Regularization
• CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration
• Analysis versus synthesis in signal priors
• How to SAIF-ly Boost Denoising Performance
• Model Selection and Estimation in Regression with Grouped Variables
• An Iterative Regularization Method for Total Variation-Based Image Restoration
• Total Generalized Variation