Multiresolution image registration based on tree data structures

Abstract

This paper presents a new approach for image registration based on the partitioning of the two source images in binary-space and quadtree structures, obtained with a maximum mutual information gain algorithm. Two different implementation approaches that differ in the level at which information is considered have been studied. The first works at pixel level using the simplified images directly, while the second works at node level dealing with the tree data structure. The obtained results show an outstanding accuracy and robustness of the proposed methods. In particular, the use of binary-space partitioned images drastically reduces the grid effects in comparison with regular downsampled images. An important advantage of our approach comes from the reduced size of the data structures corresponding to the simplified images, which makes this method appropriate to be applied in a multiresolution framework and telemedicine applications

Thanks to Dr. Narcis Coll for his help on this paper. Our work has been funded in part with Grant Numbers TIN2010-21089-C03-01 from the Spanish Government and 2009-SGR-643 from the Catalan Government