Abstract
A maximum likelihood algorithm to detect moving targets in space-time electro-optic data is derived using a model of temporally stationary and spatially nonstationary clutter statistics. Performance is evaluated in term of the probabilities of false alarm and detection. This algorithm is applied to a variety of image sequences: visible band and infrared (IR) sensors, with terrestrial and celestial clutter backgrounds. Comparison of theoretically predicted and experimentally derived statistics shows excellent agreement, validating the model and theoretical predictions.

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