Software for radio-interferometric image reconstruction with group sparsity residual regularization

This repository contains the implementation of the Group sparsity Residual regularization for Radio-interferometric Imaging (GRRI). The GRRI approach takes the groups of nonlocal image patches with similar structures as the basic unit for sparse image representation. Additionally, a low-complexity adaptive dictionary learning strategy based on principle component analysis is used for each group. Furthermore, the alternating direction method of multipliers algorithm is utilized to solve the minimization problem with group sparsity residual regularization.