Plug-and-Play Unplugged: Optimization-Free Reconstruction Using Consensus Equilibrium

DOI10.1137/17M1122451zbMath1419.94002arXiv1705.08983OpenAlexW2964215687MaRDI QIDQ5230401

Charles A. Bouman, Suhas Sreehari, Stanley H. Chan, Gregery T. Buzzard

Publication date: 22 August 2019

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1705.08983

zbMATH Keywords

ADMMtomographydenoisingMAP estimateregularized inversionconsensus optimizationmultiagent consensus equilibriumPlug-and-Play

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (10)

Bayesian Imaging Using Plug & Play Priors: When Langevin Meets Tweedie ⋮ Solving Inverse Problems by Joint Posterior Maximization with Autoencoding Prior ⋮ Image Denoising: The Deep Learning Revolution and Beyond—A Survey Paper ⋮ Deep-plug-and-play proximal Gauss-Newton method with applications to nonlinear, ill-posed inverse problems ⋮ On maximum a posteriori estimation with Plug \& Play priors and stochastic gradient descent ⋮ Convergence Results for Primal-Dual Algorithms in the Presence of Adjoint Mismatch ⋮ Compressive Computed Tomography Reconstruction through Denoising Approximate Message Passing ⋮ Unnamed Item ⋮ A support-denoiser-driven framework for single image restoration ⋮ Regularization by Denoising via Fixed-Point Projection (RED-PRO)

Uses Software

• UNLocBoX
• DnCNN

Cites Work

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