A Fast Method for Finding the Global Solution of the Regularized Structured Total Least Squares Problem for Image Deblurring

Given a linear system ${\bf A} {\bf x} \approx {\bf b}$ over the real or complex field, where both ${\bf A}$ and ${\bf b}$ are subject to noise, the total least squares (TLS) problem seeks to find a correction matrix and a correction right-hand side vector of minimal norm which makes the linear syst...

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Veröffentlicht in:	SIAM journal on matrix analysis and applications Jg. 30; H. 1; S. 419 - 443
Hauptverfasser:	Beck, Amir, Ben-Tal, Aharon, Kanzow, Christian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2008
Schlagworte:	Algebra Algebraic geometry Algorithms Boundary conditions Decomposition Exact sciences and technology Fourier transforms Industrial engineering Linear and multilinear algebra, matrix theory Mathematics Noise Nonlinear algebraic and transcendental equations Norms Numerical analysis Numerical analysis in abstract spaces Numerical analysis. Scientific computation Numerical linear algebra Optimization Regularization methods Sciences and techniques of general use Noise Optimization method Duality nonconvex optimization Boundary condition Image Optimization simultaneously diagonalizable matrices Least squares method Matrices Ill posed problem Vector unimodal functions Least squares problem Global optimum image deblurring 90C26 Algorithm Global solution 15A29 Regularization method structured total least squares Numerical analysis Linear system Linear algebra Objective function Regularization Corrections
ISSN:	0895-4798, 1095-7162
Online-Zugang:	Volltext
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