The Control Regularization-Term Iterative Algorithm For Image Deconvolution

In the paper, a new algorithm for image decovolution is proposed. We modify a parameter in the Split Bregman iterative process of Difference of Convex Algorithm in order to obtain a good trade-off between the regularization term and fidelity term. Then the algorithm gets a satisfactory approximative solution of image deconvolution, which is called Control Regularization-term Iterative algorithm. Our method has the advantage that the restored images of our method have the regularization term closer to that of the original image than that of the classical gradient descent approach. Numerical results show that our method is superior compared to other methods based on TV model.