Frame soft shrinkage operators are proximity operators

DOI10.1016/j.acha.2021.12.001OpenAlexW4205267525MaRDI QIDQ2075005

Jakob Geppert, Gerlind Plonka-Hoch

Publication date: 11 February 2022

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.01820

zbMATH Keywords

proximity operatorframe soft shrinkagemaximally cyclically monotone subdifferentialsplitting algorithms for inverse problems

Mathematics Subject Classification ID

Operator theory (47-XX) Quantum theory (81-XX)

Uses Software

• PDCO

Cites Work

• Operator splittings, Bregman methods and frame shrinkage in image processing
• Construction of compactly supported shearlet frames
• Linear convergence of iterative soft-thresholding
• Parseval proximal neural networks
• Sparse directional image representations using the discrete shearlet transform
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Deep neural network structures solving variational inequalities
• A framelet-based image inpainting algorithm
• Atomic Decomposition by Basis Pursuit
• A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
• CURVELET-WAVELET REGULARIZED SPLIT BREGMAN ITERATION FOR COMPRESSED SENSING
• The Split Bregman Method for L1-Regularized Problems
• The curvelet transform for image denoising
• Why Simple Shrinkage Is Still Relevant for Redundant Representations?
• Splitting Algorithms for the Sum of Two Nonlinear Operators
• Variational Analysis
• First-Order Methods in Optimization
• Phase retrieval for Fresnel measurements using a shearlet sparsity constraint
• Analysis versus synthesis in signal priors
• Convex analysis and monotone operator theory in Hilbert spaces

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