A Novel Correspondence Selection Technique for Affine Rigid Image Registration

This paper presents a novel technique called correspondence selection for rigid transformations in order to effectively refine keypoint matches in rigid image registration. The proposed technique mainly lies in the following two components. First, keypoint matches are ranked and selected by the distance ratio between the best match and the second best match. Second, keypoint matches are further selected by ranking the geometric similarity between corresponding keypoint triplets. These two components enhance the discriminative power of potential keypoint matches in a progressive way. The proposed technique is generally applicable to affine rigid image registration. Experiments have been conducted using a set of benchmark datasets in the field of image registration, indicating that the proposed technique is very effective and achieves the state-of-the-art performance in refining keypoint matches for affine rigid image registration.