An Iterative Algorithm For Solving Underdetermined Linear Systems In Computed Tomography

Document Type

Presentation

Presentation Date

11-14-2013

Abstract or Description

The sparse solutions of an underdetermined linear system Ax = b under certain condition can be obtained by solving a constrained l1-minimization problem: min ||x||1 subject to Ax = b. An generalized l1 greedy algorithm is proposed. It is implemented as a generalized total variation minimization for reconstruction of medical images with sparse gradients in computed tomography. Numerical experiments are also given to illustrate the advantage of the new iterative algorithm.

Sponsorship/Conference/Institution

Institut für Numerische Mathematik und Optimierung Technische Universität Bergakademie

Location

Freiberg, Germany

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