Image Restoration with Regularization Convex Optimization Approach

In this paper, Tikhonov regularization with l-curve parameter estimation as convex optimization problem has been proposed in image restoration as a solution of ill-posed problem stem from sparse and large scale blurring matrix which has many singular values of different orders of magnitude close to the origin. Also, since the restored image is so sensitive to initial guess (start point) of optimization algorithm, a new schema for feasible set and feasible start point has been proposed. Some numerical results show the efficiency of the proposed algorithm in comparison with previous proposed methods.

Keywords:

Image restoration , convex optimization , Tikhonov regularization , l-curve estimation