A Modified Newton Projection Method for -Regularized Least Squares Image Deblurring

In recent years, -regularized least squares have become a popular approach to image deblurring due to the edge-preserving property of the -norm. In this paper, we consider the nonnegatively constrained quadratic program reformulation of the -regularized least squares problem and we propose to solve it by an efficient modified Newton projection method only requiring matrix-vector operations. This approach favors nonnegative solutions without explicitly imposing any constraints in the -regularized least squares problem. Experimental results on image deblurring test problems indicate that the developed approach performs well in comparison with state-of-the-art methods.