A new image motion estimation algorithm based on the EM technique

This paper focuses on the presentation and implementation of a new iterative algorithm for image motion coefficient estimation from noisy measurements based on the expectation-maximization (EM) technique. We also compare this algorithm with two other robust iterative algorithms. We represent the motion field by a (unitary) series expansion to obtain the motion coefficients, and show this characterization to have several virtues. First, an inherent property of motion, referred to as smoothness, is imposed. Second, the nonuniform motion estimation is reduced to the estimation of a few coefficients using the low-pass property of the motion. Finally, the motion estimation can be accomplished without the need for a motion model; in the events for which the motion model is completely unknown, the DCT representation is shown to be very effective in describing the true motion