In this talk we describe details of new state-of-the-art Krylov subspace iterative solvers that are implemented in our MATLAB software package IR Tools. In particular, we describe hybrid Krylov-subspace-based regularization approaches that combine matrix factorization methods with iterative solvers. The methods are very efficient for large scale problems, and can also incorporate methods to automatically estimate regularization parameters. We also show how the approaches can be adapted to enforce sparsity and nonnegativity.

This presentation is part of Minisymposium “MS34 - Numerical Linear Algebra techniques for Image Restoration and Reconstruction (2 parts)”
organized by: Caterina Fenu (University of Cagliari) , Marco Donatelli (University of Insubria) .

Authors:

Silvia Gazzola (University of Bath)

Per Christian Hansen (Technical University of Denmark)

James Nagy (Emory University)

Keywords:

computed tomography, image reconstruction, inverse problems, numerical linear algebra