Simultaneous motion estimation and filtering of image sequences

We present an algorithm to simultaneously estimate multiple-frame motions and filter image sequences. The relative motion d/sub k/(x) between the reference frame s(x) and the kth frame s(x-d/sub k/(x)) in the presence of additive white Gaussian noise (AWGN) is estimated using the maximum-likelihood (ML) principle. The reference frame is also filtered in the linear minimum mean square error (LMMSE) sense during the process of motion estimation. Simulation experiments are performed using the affine motion model to illustrate the performance of this method.