Optical Flow of Small Objects Using Wavelets, Bootstrap Methods, and Synthetic Discriminant Filters
نویسندگان
چکیده
In 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 (SDF's). 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.
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