Second-Order Total Variation and Primal-Dual Algorithm for CT Image Reconstruction

Abstract

In this paper, we proposed a regularization model based on second-order total variation for CT image reconstruction, which could eliminate the 'staircase' caused by total variation (TV) minimization. Moreover, some properties of second-order total variation were investigated, and a primal-dual algorithm for the proposed model was presented. Some numerical experiments for various projection data were conducted to demonstrate the efficiency of the proposed model and algorithm.