Abstract
A frequency domain implementation of the Optimal Trade-off Maximum Average Correlation Height (OT-MACH) filter has been optimized to classify target vehicles acquired from a Forward Looking Infra Red (FLIR) sensor. The clutter noise does not have a white spectrum and models employing the power spectral density of the background clutter require a predefined threshold. A method of automatically adjusting the noise model in the filter by using the input image statistical information has been introduced. Parameter surfaces for the remaining OT-MACH variables are calculated in order to determine optimal operating conditions for the view independent recognition of vehicles in highly cluttered FLIR imagery.
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