Motion Compensation Based on Robust Global Motion Estimation: Experiments and Applications

A robust and general method for image alignment is proposed in this paper. The industrial constraints are the possible large and irregular camera motion, some possible occlusions or moving objects in the images and some blur or motion blur. Images are taken from an Unmanned Aerial Vehicle or a long-range camera. Given this context, a similarity transformation is estimated. An hybrid algorithm is proposed, implemented in a pyramidal way, and combining direct and feature-based approaches. Some detailed experiments in this paper show the robustness and efficiency of the proposed algorithm. Results of some applications of this method are given, like image stabilisation, image mosaicing and road surveillance.