Wavelet Expansion and High-order Regularization for Multiscale Fluid-motion Estimation

We consider a novel optic flow estimation algorithm based on a wavelet expansion of the velocity field. In particular, we propose an efficient gradient-based estimation algorithm which naturally encompasses the estimation process into a multiresolution framework while avoiding most of the drawbacks common to this kind of hierarchical methods. We then emphasize that the proposed methodology is well-suited to the practical implementation of high-order regularizations. The powerfulness of the proposed algorithm and regularization schemes are finally assessed by simulation results on challenging image sequence of turbulent fluids