Multiresolution image registration based on tree data structures

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.

Graphical abstractNew 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.Figure optionsDownload full-size imageDownload as PowerPoint slideResearch highlights► We present a new approach for the registration of partitioned images. ► We analyze the behavior of binary-space (BSP) and quadtree partition structures. ► The robustness and computational cost of two implementation alternatives are analyzed. ► Results show that the proposed methods are outstandingly accurate and robust. ► This method is appropriated for multiresolution and telemedicine applications.