Alternating direction method of multipliers applied to medical image restoration

TL;DR

This paper explores how the regularization and penalty parameters in ADMM affect medical image restoration quality, providing insights for optimal parameter selection to improve image clarity.

Contribution

It systematically analyzes the impact of ADMM parameters on medical image restoration quality, offering guidelines for optimal parameter tuning.

Findings

Optimal regularization parameter is approximately 10 to 20.

Decreasing the penalty parameter causes image blurring.

Maximal structural similarity index achieved at specific parameter values.

Abstract

We investigate the effects of the regularization parameter for the norm () and penalty parameter () in the alternating direction method of multipliers (ADMM) on the quality of restored medical images. Simulation studies are performed using images degraded by a point spread function (PSF) and Gaussian noise. The j-th column of the system matrix () is calculated by convolving the image with unity at pixel j and zero at all other pixels and the PSF. The simulation studies show that the mean structural similarity index is maximal when is approximately 10 to 20, where , with and being the transpose of A and the observed data, respectively. The restored image became blurred with a decrease in . This study will be useful for identifying optimal parameter values in the ADMM when applied to medical image restoration.