Convex Image Denoising via Non-Convex Regularization

DOI10.1007/978-3-319-18461-6_53zbMath1444.94015OpenAlexW1914015964MaRDI QIDQ3300347

Alessandro Lanza, Fiorella Sgallari, Serena Morigi

Publication date: 28 July 2020

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-18461-6_53

zbMATH Keywords

image denoisingnon-convex non-smooth regularizationalternating directions method of multipliers

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Discrete approximations in optimal control (49M25) Inverse problems in optimal control (49N45)

Related Items (11)

Sparsity-aided variational mesh restoration ⋮ Convex image denoising via non-convex regularization with parameter selection ⋮ Convex non-convex image segmentation ⋮ Deep-plug-and-play proximal Gauss-Newton method with applications to nonlinear, ill-posed inverse problems ⋮ Image restoration via the adaptive \(TV^p\) regularization ⋮ Sparsity-Inducing Nonconvex Nonseparable Regularization for Convex Image Processing ⋮ Convex non-convex segmentation of scalar fields over arbitrary triangulated surfaces ⋮ A convex-nonconvex variational method for the additive decomposition of functions on surfaces ⋮ Nonconvex and nonsmooth sparse optimization via adaptively iterative reweighted methods ⋮ Automatic parameter selection based on residual whiteness for convex non-convex variational restoration ⋮ A Variational Approach to Additive Image Decomposition into Structure, Harmonic, and Oscillatory Components

Cites Work

• Nonlinear total variation based noise removal algorithms
• Tikhonov regularization of large linear problems
• Tikhonov regularization and the L-curve for large discrete ill-posed problems
• Constrained TV\(_p\)-\(\ell_2\) model for image restoration
• Constrained Total Variation Deblurring Models and Fast Algorithms Based on Alternating Direction Method of Multipliers
• Sparse Signal Estimation by Maximally Sparse Convex Optimization
• Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization
• Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers
• On $\ell_1$ Data Fitting and Concave Regularization for Image Recovery
• Efficient Minimization Method for a Generalized Total Variation Functional
• Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction

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