Nonuniform image motion estimation using the maximum a posteriori principle

An iterative scheme for frame-to-frame motion estimation from a pair of noisy images is established. The algorithm is developed by assuming that the Karhunen-Loeve coefficients of the motion vector waveform are zero mean and Gaussian random variables. Following the derivation of the generalized maximum likelihood (GML) algorithm, and invoking the maximum a posteriori (MAP) criterion, an iterative motion estimator is developed. A linear analysis of the algorithm is presented, and the convergence of the algorithm is discussed. Simulation experiments are performed and comparisons are made with the GML algorithm the algorithm reported by A.N. Netravali and J.D. Robbins (1979), and the scheme developed by K.P.G. Horn and G.G. Schunck (1981).<
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