A feasible direction method for image restoration
type: Item
instance of: scholarly article
title: A feasible direction method for image restoration
zbMATH Open document ID: 1261.90055
published in: Optimization Letters
publication date: 2012-12-28T00:00:00Z
Mathematics Subject Classification ID: 90C30
Mathematics Subject Classification ID: 90C90
zbMATH DE Number: 6119200
zbMATH Keywords: image restoration
zbMATH Keywords: constrained minimization
zbMATH Keywords: feasible direction method
zbMATH Keywords: truncated conjugate gradient method
author: G. Landi
author: E. Loli Piccolomini
describes a project that uses: LSTRS
MaRDI profile type: Publication
full work available at URL: s11590-011-0378-z
OpenAlex ID: W2110921065
cites work: Q3843144
cites work: Q3151174
cites work: Trust Region Methods
cites work: Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems
cites work: Recovery of Blocky Images from Noisy and Blurred Data
cites work: The trust region subproblem and semidefinite programming*
cites work: A Trust Region Method for Norm Constrained Problems
cites work: A trust-region strategy for minimization on arbitrary domains
cites work: Numerical Optimization
cites work: Restoration of degraded images with maximum entropy
cites work: Iterative Solution of Nonlinear Equations in Several Variables
cites work: A semidefinite framework for trust region subproblems with applications to large scale minimization
cites work: A new matrix-free algorithm for the large-scale trust-region subproblem
cites work: Algorithm 873
cites work: Nonlinear total variation based noise removal algorithms
cites work: Iterative regularization algorithms for constrained image deblurring on graphics processors
cites work: GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems
cites work: The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
cites work: Q4125663
cites work: Computational Methods for Inverse Problems
cites work: Iterative Methods for Total Variation Denoising
cites work: Fast, robust total variation-based reconstruction of noisy, blurred images
cites work: Q5591247
DOI: 10.1007/S11590-011-0378-Z
description: scientific article; zbMATH DE number 6119200