A new stereo algorithm based on snakes

As part of the ongoing activities for the European space mission BepiColombo to Mercury, a new stereo-matching algorithm is here proposed: this algorithm uses deformable surfaces, or snakes, to find a dense disparity map. Subjectto both external and internal forces, respectively represented by the similarity function and by smoothness constraints onthe disparity map, a "deformable" disparity map evolve sfrom an initial approximate state to an optimal one in which the algorithm has reached convergence. This algorithm is expected to provide one of the image matching tools for the Digital Terrain Model generation procedure that will be used by the BepiColombo stere ocamera. To check the algorithm, tests have been performed on synthetic images derived from 3D models of geological features relevant to planetary science. The results show thatit is possible to obtain an image measurement accuracy comparable to the one attainable with the Least Squares Matching algorithm. In addition, less object smoothing can be obtained since the object points are not derived by alarge scale averaging over a terrain patch, as for example, in area-based methods; this means that more details of theterrain can be captured. Finally, because of the continuityconstraint, this method is also expected to be robust in caseof blunders in the reconstruction of the parallax field. © 2011 American Society for Photogrammetryand Remote Sensing.