<title>Maximum likelihood estimation of affine-modeled image motion</title>

Abstract

© 1991 SPIE. All rights reserved. This paper is concerned with the estimation of the image motion field from a pair of consecutive noisy frames. The maximum likelihood principle is invoked for estimating the nonrandom but unknown displacement function. In our developments, we consider processing both of the observed images (jointly) through a 2x2 noncausal matrix filter. The design of this matrix filter depends on the assumed values of the parameters for the displacement function. The analysis presented is the extension and generalization of the work originally established by Stuller who studied the problem of maximum likelihood estimation of variable time delay. The developments are specialized to the case for which the motion field is modeled by an affine transformation. Simulations are performed which indicate the validity of the estimator in the presence of noise. Results of the simulations are presented.