<title>Hierarchical multiresolution technique for image registration</title>

Abstract

Our aim is to derive a fully automatic method for highly accurate registration of large low quality images of objects in a distance. A global geometric transformation is used to model the displacement; the parameters of the transformation are then determined by fitting to a field of local displacement estimates which are computed by normalized local cross-correlation matching. Because the displacements can be large, direct matching would be computationally too expensive. This can be resolved by using image pyramids and hierarchical refining of the estimate of transformation describing the displacement. Replacing the standard image pyramids by wavelet decompositions of images is studied in this paper. The proposed approach is based on merging the local displacement estimates from different subbands and applying an iterative algorithm which fits the transformation only to those local estimates that are more likely to be correct. The result of tests on both genuine and artificially created pairs of misaligned images are presented and different possible strategies and suitability of particular wavelet bases are discussed.