A Reweighted Total Variation Algorithm with the Alternating Direction Method for Computed Tomography

Xiezhang Li^*, Jiehua Zhu

Department of Mathematical Sciences, Georgia Southern University, Statesboro, GA, USA.

DOI: 10.4236/act.2019.81001                

Abstract

A variety of alternating direction methods have been proposed for solving a class of optimization problems. The applications in computed tomography (CT) perform well in image reconstruction. The reweighted schemes were applied in l₁-norm and total variation minimization for signal and image recovery to improve the convergence of algorithms. In this paper, we present a reweighted total variation algorithm using the alternating direction method (ADM) for image reconstruction in CT. The numerical experiments for ADM demonstrate that adding reweighted strategy reduces the computation time effectively and improves the quality of reconstructed images as well.

Keywords

Computed Tomography, Nonmonotone Alternating Direction Algorithm, Reweighted Algorithm

Conflicts of Interest

The authors declare no conflicts of interest.

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