Second order optimization of mutual information for real-time image registration

International audienceIn this paper we present a direct image registration approach that uses Mutual Information (MI) as a metric for alignment. The proposed approach is robust, real-time and gives an accurate estimation of a set of 2D motion parameters. MI is a measure of the quantity of information shared by signals. Although it has the ability to perform robust alignment with illumination changes, multi-modality and partial occlusions, few works propose MI-based applications related to spatio-temporal image registration or object tracking in image sequences due to some optimization problems that we will explain. In this work, we propose a new optimization method that is adapted to the MI cost function and gives a practical solution for real time tracking. We show that by refining the computation of the Hessian matrix and using a specific optimization approach, the registration results are far more robust and accurate than the existing solutions while the computation is cheaper. A new approach is also proposed to speed up the computation of the derivatives and keep an equivalent optimization efficiency. To validate the advantages of the proposed approach, several experiments are performed