A projected Newton-CG method for nonnegative astronomical image deblurring

Abstract

Astronomical images are usually assumed to be corrupted by a space-invariant Point Spread Function and Poisson noise. In this paper we propose an original projected inexact Newton method for the solution of the constrained nonnegative minimization problem arising from image deblurring. The problem is ill-posed and the objective function must be regularized. The inner system is inexactly solved by few Conjugate Gradient iterations. The convergence of the method is proved and its efficiency is tested on simulated astronomical blurred images. The results show that the method produces good reconstructed images at low computational cost.