Quantifying infrared target signature evolution using AM-FM features

In this paper we combine a new method of measuring infrared target signature evolution with current research and developmental tracking algorithms. Thermal images are decomposed by a set of Gabor filters and demodulated to produce a set of spatiospectrally localized AM-FM functions corresponding to oriented texture regions from within the original image. Critical updates are detected and issued to a particle filter based tracker, operating only on a modulation domain target model, by applying an empirically determined threshold to a new target evolution measurement introduced in this paper. We achieve results comparable to several other theoretical tracking algorithms at a significantly reduced computational cost by eliminating the need to perform parallel tracking in both the pixel and modulation domains.