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Proceedings Paper

Maximum likelihood estimation of affine-modeled image motion
Author(s): Samir J. Shaltaf; Nader M. Namazi
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Paper Abstract

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 2 X 2 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.

Paper Details

Date Published: 1 December 1991
PDF: 12 pages
Proc. SPIE 1567, Applications of Digital Image Processing XIV, (1 December 1991); doi: 10.1117/12.50849
Show Author Affiliations
Samir J. Shaltaf, Michigan Technological Univ. (United States)
Nader M. Namazi, Michigan Technological Univ. (United States)


Published in SPIE Proceedings Vol. 1567:
Applications of Digital Image Processing XIV
Andrew G. Tescher, Editor(s)

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