Generalized methods and solvers for noise removal from piecewise constant signals. II. New methods

DOI10.1098/rspa.2010.0674zbMath1239.94019arXiv1012.5095OpenAlexW1480782025WikidataQ51517624 ScholiaQ51517624MaRDI QIDQ2889165

Max A. Little, Nick S. Jones

Publication date: 4 June 2012

Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1012.5095

zbMATH Keywords

shiftedgejumpchangelevelstep

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (11)

Graph signal denoising using \(t\)-shrinkage priors ⋮ Constrained energy variation for change point detection ⋮ Robust change point detection method via adaptive LAD-Lasso ⋮ Recursive reconstruction of piecewise constant signals by minimization of an energy function ⋮ Signal processing for molecular and cellular biological physics: an emerging field ⋮ Optimal nonlinear signal approximations based on piecewise constant functions ⋮ Jump-penalized least absolute values estimation of scalar or circle-valued signals ⋮ The Development of an Information Criterion for Change-Point Analysis ⋮ Topological data analysis for true step detection in periodic piecewise constant signals ⋮ Iterative Potts minimization for the recovery of signals with discontinuities from indirect measurements: the multivariate case ⋮ Smoothing for signals with discontinuities using higher order Mumford-Shah models

Cites Work

• Nonlinear total variation based noise removal algorithms
• Splines in higher order TV regularization
• Haar wavelet-based technique for sharp jumps classification
• New multiscale transforms, minimum total variation synthesis: Applications to edge-preserving image reconstruction
• Image restoration with discrete constrained total variation. I: Fast and exact optimization
• Pathwise coordinate optimization
• Piecewise linear regularized solution paths
• Modern statistical estimation via oracle inequalities
• $\ell_1$ Trend Filtering
• Singularity detection and processing with wavelets
• Quantile smoothing splines
• On the Equivalence of Soft Wavelet Shrinkage, Total Variation Diffusion, Total Variation Regularization, and SIDEs
• Jump and sharp cusp detection by wavelets
• Segmentation of well logs by maximum-likelihood estimation

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