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

Pierre Dérian (1) , Patrick Héas (1) , Cédric Herzet (2) , Etienne Mémin (1)

1 FLUMINANCE - Fluid Flow Analysis, Description and Control from Image Sequences
2 TEMICS - Digital image processing, modeling and communication

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.

Domains: Computer Vision and Pattern Recognition [cs.CV]

Pierre Dérian, Patrick Héas, Cédric Herzet, Etienne Mémin. Wavelet Expansion and High-order Regularization for Multiscale Fluid-motion Estimation. [Research Report] RR-7348, INRIA. 2010. ⟨inria-00505780v2⟩