Abstract

Measurements of an object viewed at low-light levels through weak atmospheric turbulence are modeled mathematically as a time-space doubly stochastic Poisson process in which the intensity function moves randomly in time but is otherwise undistorted. This model is used with the maximum-likelihood method of statistics to derive a new method for forming an image of the object. A simple computer simulation of a moving one-dimensional binary star suggests that improved images may be produced by this method in comparison with others that have been suggested in the literature, but it remains to be demonstrated that this improvement is realized in practice with real imagery data.

© 1990 Optical Society of America

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