A new estimation of blur in the blind restoration problem

The blind restoration problem is a well-known ill-posed problem. Both regularization and Bayesian approaches define the solution as the minimum of an appropriate energy function. The energy function has to take into consideration that the ideal image presents some discontinuities, and that close discontinuities should not be parallel. In this paper we propose a new estimation for the blur. We define as solution the blur that, used as known in the restoration of a image, permits to obtain the image that better fits our a priori knowledge of ideal image. We call this estimation IMAP (indirect maximum a priori). To compute the IMAP estimation we use a SA (simulated annealing) algorithm, where the restoration of image is performed by the CATILED (convex approximation technique for interacting line element deblurring) algorithm. The experimental results show the goodness of the IMAP estimation.