Optical Flow of Small Objects Using Wavelets, Bootstrap Methods, and Synthetic Discriminant Filters

The the look down shoot down scenario, the next generation of air to surface missiles will rely on IR sensors and advanced signal processing to detect small or point targets in highly cluttered and noisy environments. In this paper we present a novel wavelet detection algorithm which incorporates adaptive CFAR detection statistics using the bootstrap method. Following detection, the estimate of interframe optical flow is made using synthetic discriminant filters SDFs. The detection coupled with the new optical flow estimate will enable higher performance in tracking small maneuverable targets. Results for the wavelet bootstrap detection are presented and compared to a conventional matched filter.