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 1l-minimization and other iteratively reweighted 1l-algorithms when applying for image reconstruction from CS