Image motion estimation from blurred and noisy image sequences

A new iterative algorithm to estimate image motion from noisy-blurred image sequences is developed, presented and evaluated. This algorithm seeks the maximum-likelihood estimate of image motion coefficients in an arbitrary transformed domain directly from noisy-blurred data. The range of the convergence parameters which control the speed of convergence is also presented. Simulation experiments demonstrate the validity of the motion estimator. Additional experiments investigate the sensitivity of the algorithm to the extent of blur. We also show the potential application of the estimated motion to image sequence restoration.