Implementation of the regularized structured total least squares algorithms for blind image deblurring

DOI10.1016/j.laa.2004.07.006zbMath1060.94502OpenAlexW1990245893MaRDI QIDQ1888346

A. Kalsi, Dianne P. O'Leary, Nicola Mastronardi, Philippe Lemmerling, Sabine Van Huffel

Publication date: 23 November 2004

Published in: Linear Algebra and its Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.laa.2004.07.006

zbMATH Keywords

Tikhonov regularizationGeneralized Schur algorithmStructured total least squaresImage deblurringBlock Toeplitz matrixDisplacement rank

Mathematics Subject Classification ID

Related Items (4)

Fast deconvolution with approximated PSF by RSTLS with antireflective boundary conditions ⋮ The generalized Schur algorithm and some applications ⋮ Fast robust regression algorithms for problems with Toeplitz structure ⋮ Reaction-diffusion equation based image restoration

Uses Software

• Regularization tools
• UTV
• VanHuffel

Cites Work

• An Analysis of the Total Least Squares Problem
• A new approach to constrained total least squares image restoration
• Deconvolution and regularization with Toeplitz matrices
• A regularized structured total least squares algorithm for high-resolution image reconstruction
• Fast Structured Total Least Squares Algorithm for Solving the Basic Deconvolution Problem
• Stabilized hyperbolic Householder transformations
• Fast regularized structured total least squares algorithm for solving the basic deconvolution problem
• Hyperbolic householder transformations
• Hyperbolic Householder Transforms
• Rank-Deficient and Discrete Ill-Posed Problems
• Blind Deconvolution Using a Regularized Structured Total Least Norm Algorithm
• A Note on Downdating the Cholesky Factorization
• Total Least Norm Formulation and Solution for Structured Problems
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