An efficient iteratively reweighted L1-minimization for image reconstruction from compressed sensing

Abstract

We proposed a simple and efficient iteratively reweighted algorithm to improve the recovery performance for image reconstruction from compressive sensing (CS). The numerical experiential results demonstrate that the new proposed method outperforms in image quality and computation complexity, compared with standard 1 l-minimization and other iteratively reweighted 1 l-algorithms when applying for image reconstruction from CS.