Large-scale methods in image deblurring

Authors:
Per Christian Hansen;Toke Koldborg Jensen
Affiliations:
Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark;TNM Consult, Herlev, Denmark
Venue:
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Year:
2006

Citing 3
Cited 1

Fundamentals of digital image processing

Fundamentals of digital image processing
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion

Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms)

Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms)

A meshless method for solving nonlinear two-dimensional integral equations of the second kind on non-rectangular domains using radial basis functions with error analysis

Journal of Computational and Applied Mathematics

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Abstract

We use the two-dimensional DCT to study several properties of reconstructed images computed by regularizing iterations, that is, Krylov subspace methods applied to discrete ill-posed problems. The regularization in these methods is obtained via the projection onto the associated Krylov subspace. We focus on CGLS/LSQR, GMRES, and RRGMRES, as well as MINRES and MR-II in the symmetric case.