Iterative Potts minimization for the recovery of signals with discontinuities from indirect measurements: the multivariate case
DOI10.1007/s10208-020-09466-9zbMath1468.94019arXiv1812.00862OpenAlexW3039927614MaRDI QIDQ2040452
Martin Storath, Andreas Weinmann, Lukas Kiefer
Publication date: 14 July 2021
Published in: Foundations of Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1812.00862
Radon transformdeconvolutionPotts modelimage segmentationill-posed inverse problemspiecewise constant Mumford-Shah modeljoint reconstruction and segmentationmajorization-minimization methods
Nonconvex programming, global optimization (90C26) Numerical optimization and variational techniques (65K10) Computing methodologies for image processing (68U10) Dynamic programming (90C39) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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- Nonlinear total variation based noise removal algorithms
- Global minimization for continuous multiphase partitioning problems using a dual approach
- Iterative hard thresholding methods for \(l_0\) regularized convex cone programming
- A Mumford-Shah level-set approach for the inversion and segmentation of SPECT/CT data
- Iterative thresholding meets free-discontinuity problems
- Iterative hard thresholding for compressed sensing
- Iterative thresholding for sparse approximations
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- A Mumford-Shah level-set approach for the inversion and segmentation of X-ray tomography data
- Consistencies and rates of convergence of jump-penalized least squares estimators
- A multiphase level set framework for image segmentation using the Mumford and Shah model
- Completely convex formulation of the Chan-Vese image segmentation model
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Iteration-complexity of first-order penalty methods for convex programming
- Jump estimation in inverse regression
- Existence of minimizers of the Mumford-Shah functional with singular operators and unbounded data
- Smoothing for signals with discontinuities using higher order Mumford-Shah models
- AIR tools -- a MATLAB package of algebraic iterative reconstruction methods
- Thresholding implied by truncated quadratic regularization
- Linearly Constrained Nonsmooth and Nonconvex Minimization
- Regularization Properties of Mumford--Shah-Type Functionals with Perimeter and Norm Constraints for Linear Ill-Posed Problems
- Stable Image Reconstruction Using Total Variation Minimization
- Tight Convex Relaxations for Vector-Valued Labeling
- Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory
- Generalized methods and solvers for noise removal from piecewise constant signals. II. New methods
- Optimal approximations by piecewise smooth functions and associated variational problems
- Regularization of ill-posed Mumford–Shah models with perimeter penalization
- A Mumford–Shah-Like Method for Limited Data Tomography with an Application to Electron Tomography
- Continuous Multiclass Labeling Approaches and Algorithms
- Approximation of functional depending on jumps by elliptic functional via t-convergence
- Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models
- An algorithmic framework for Mumford–Shah regularization of inverse problems in imaging
- Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction?
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Splitting Algorithms for the Sum of Two Nonlinear Operators
- Finite-differences discretizations of the mumford-shah functional
- Active contours without edges
- Jump-Sparse and Sparse Recovery Using Potts Functionals
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
- Smoothers for Discontinuous Signals
- Image Segmentation by Variational Methods: Mumford and Shah Functional and the Discrete Approximations
- A Convex Approach to Minimal Partitions
- Optimal Detection of Changepoints With a Linear Computational Cost
- $\ell _0$ Minimization for wavelet frame based image restoration
- Fast Partitioning of Vector-Valued Images
- Joint image reconstruction and segmentation using the Potts model
- Iterative Potts and Blake–Zisserman minimization for the recovery of functions with discontinuities from indirect measurements
- Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction
- Near-Optimal Compressed Sensing Guarantees for Total Variation Minimization
- Sparse Approximation via Penalty Decomposition Methods
- Regularizing properties of the Mumford–Shah functional for imaging applications
- Efficient Reconstruction of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization
- Computer Vision - ECCV 2004
- Multiscale Change Point Inference
- An Iteration Formula for Fredholm Integral Equations of the First Kind