On the improvement of image registration for high accuracy super-resolution

Accurate image registration plays a preponderant role in image super-resolution methods and in the related literature landmark-based registration methods have gained increasing acceptance in this framework. However, their solution relies on point correspondences and on least squares estimation of the registration parameters neces-sitating further improvement. In this work, a maximum a posteriori scheme for image super-resolution is presented where the image registration part is accomplished in two steps. At first, the low-resolution images are registered by establishing correspondences between robust SIFT features. In the second step, the estimation of the registration parameters is fine-tuned along with the estimation of the high resolution image, in an iterative procedure, using the maximization of the mutual information criterion. Numerical results showed that the reconstructed image is consistently of higher quality than in standard MAP-based methods employing only landmarks. Index Terms — Super-resolution, image registration, mutual in-formation, scale invariant feature transform (SIFT). 1