The solution of large-scale ill-posed problems that arise in image
restoration problems has recently received considerable attention. Many of
the available solution methods are based on Tikhonov regularization. This talk presents new iterative methods for Tikhonov regularization that explore the
connection between orthogonal polynomials, Gauss quadrature and Lanczos bidiagonalization. Methods for unconstrained and constrained regularization problems will be discussed and comparisons with other available iterative
methods will be presented.
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