Until now, most optical pattern recognition filters have been designed to process one image at a time. However, in image sequences, successive frames are highly correlated, so that it is useful to take this correlation into account while designing the filter. We develop a target tracking processor following this method. The images are assumed to consist of a moving object appearing against a moving background. A model that takes into account two successive frames is designed. From this model we determine the maximum-likelihood processor for tracking the object from one frame to the next. Since this processor is based on correlation operations, it could be implemented on a hybrid optoelectronic system that makes use of the rapidity of optical correlation.
© 1997 Optical Society of America
Original Manuscript: December 16, 1996
Revised Manuscript: June 23, 1997
Manuscript Accepted: July 1, 1997
Published: December 1, 1997
François Goudail and Philippe Réfrégier, "Optimal target tracking on image sequences with a deterministic background," J. Opt. Soc. Am. A 14, 3197-3207 (1997)