4 October 1999 Detection and clutter rejection in image sequences based on multivariate conditional probability
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Abstract
A method of detecting dim targets in highly-cluttered time- varying image sequences is presented, where reliable clutter rejection is achieved by calibrating the multivariate statistics of a small number of generic space-time filters. The targets have sufficiently low SCR that a track-before- detect method is required. For targets where there is little prior information on velocity, a large number of filters is generally required to achieve a high response relative to the background. In the method described here, instead of applying thresholds to individual filters, joint filter statistics are used to estimate conditional threshold exceedance probabilities. A smaller number of more generic filters are applied, which are not finely tuned to targets but which characterize aspects of both targets and clutter. Potential targets are cued based on a non-parametric estimate of the probability of occurrence of similar clutter. Constant false alarm rates are inherent in the method. The method is demonstrated on examples of real forward-looking imagery of the sea surface, where glint is a source of strong clutter. Dim targets are distinguished form clutter by using the joint statistics of three variables: a constant-intensity blob filter, a filter tuned to sea glint flashes, and the vertical image coordinate.
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Graham H. Watson, Graham H. Watson, Sharon K. Watson, Sharon K. Watson, } "Detection and clutter rejection in image sequences based on multivariate conditional probability", Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); doi: 10.1117/12.364012; https://doi.org/10.1117/12.364012
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