Superiorized iteration based on proximal point method and its application to XCT image reconstruction

TL;DR

This paper introduces a novel superiorized iteration method using the proximal point approach, which improves convergence and image quality in XCT reconstruction.

Contribution

It proposes a new perturbation strategy based on the proximal point method for superiorized iteration, enhancing convergence and image quality in XCT.

Findings

Improved convergence rate in XCT image reconstruction

Enhanced image quality with the proposed method

Effective perturbation computation using proximal point approach

Abstract

In this paper, we investigate how to determine a better perturbation for superiorized iteration. We propose to seek the perturbation by proximal point method. In our method, the direction and amount of perturbation are computed simultaneously. The convergence conditions are also discussed for bounded perterbation resilence iteration. Numerical experiments on simulated XCT projection data show that the proposed method improves the convergence rate and the image quality.