Affine registration with multi-scale autoconvolution

In this paper we propose a novel method for the recovery of affine transformation parameters between two images. Registration is achieved without separate feature extraction by directly utilizing the intensity distribution of the images. The method can also be used for matching point sets under affine transformations. Our approach is based on the same probabilistic interpretation of the image function as the recently introduced multi-scale autoconvolution (MSA) transform. Here we describe how the framework may be used in image registration and present two variants of the method for practical implementation. The proposed method is experimented with binary and grayscale images and compared with other non-feature-based registration methods. The experiments show that the new method can efficiently align images of isolated objects and is relatively robust.