Smoothers for Discontinuous Signals

DOI10.1080/10485250211388zbMath1019.62090OpenAlexW1973897753MaRDI QIDQ4805753

Gerhard Winkler, Volkmar Liebscher

Publication date: 8 May 2003

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485250211388

zbMATH Keywords

nonlinear filterssignal processingPotts modelimage analysisedge preserving smoothing

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Inference from spatial processes (62M30) Bayesian inference (62F15) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (15)

Mumford-Shah and Potts regularization for manifold-valued data ⋮ An algorithmic framework for Mumford–Shah regularization of inverse problems in imaging ⋮ Adaptive risk bounds in univariate total variation denoising and trend filtering ⋮ Complexity \(L^0\)-penalized \(M\)-estimation: consistency in more dimensions ⋮ Jump-penalized least absolute values estimation of scalar or circle-valued signals ⋮ MULTI-FACTOR JUMP-DIFFUSION MODELS OF ELECTRICITY PRICES ⋮ An Algorithm for Second Order Mumford--Shah Models Based on a Taylor Jet Formulation ⋮ Non-smooth Variational Regularization for Processing Manifold-Valued Data ⋮ Approximate \(\ell_0\)-penalized estimation of piecewise-constant signals on graphs ⋮ Consistencies and rates of convergence of jump-penalized least squares estimators ⋮ Iterative Potts minimization for the recovery of signals with discontinuities from indirect measurements: the multivariate case ⋮ Smooth functions and local extreme values ⋮ Smoothing for signals with discontinuities using higher order Mumford-Shah models ⋮ Multi-channel Potts-based reconstruction for multi-spectral computed tomography ⋮ Multiscale Change Point Inference

Uses Software

• AWS

Cites Work

• Simulated annealing - to cool or not
• Robust priors for smoothing and image restoration
• Choosing a kernel regression estimator. With comments and a rejoinder by the authors
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Edge-Preserving Smoothers for Image Processing
• A nonlinear gaussian filter applied to images with discontinuities
• Robust Statistics
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