Noise insensitive image motion estimation using cumulants

A class of algorithms is presented that estimate the displacement vector from two successive image frames. The frames are assumed to be corrupted by Gaussian (perhaps correlated) noises of unknown covariance. Viewing image motion estimation as a 2-D time delay estimation problem, the displacement vector of a moving object is estimated by solving linear equations involving third-order auto-cumulants and cross-cumulants. Additionally, a block-matching type algorithm is developed which follows from a cumulant-error optimality criterion. Finally, using a recursive algorithm the displacement vector for each pel is estimated by minimizing a 2-D fourth-order cumulant criterion. Simulation results are presented and discussed.