Abstract
This paper introduces a computationally efficient algorithm for synthesis of a distortion tolerant correlation filter and associated threshold, denoted collectively as the enhanced matched filter (EMF). Application areas of EMF include imagery based automatic target detection and recognition and biometrics. The EMF is synthesized from a set of training images characterizing the target of interest within the expected distortion range. A distinguishing feature of EMF is the ascribed threshold, which is a byproduct of the filter computation process and does not rely on nontarget trainers. The EMF performance is compared to that of the synthetic discriminant function using realistic test scenarios.
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