Binary tomography reconstruction algorithm based on the spectral projected gradient optimization

Abstract

In this paper we propose an optimization approach based on the Spectral Projected Gradient (SPG) method for solving the binary tomography reconstruction problem. Using a convex-concave regularization we treat the reconstruction problem as a convex and box constrained optimization problem which is suitable to solve by SPG method. Experimental results on the limited set of test problems show that the new method has competitive reconstruction performance in comparison with a well known non-deterministic simulated annealing approach. In addition, its capability to apply other regularization terms gives to this deterministic method a desirable properties.