Adaptive Dim Point Target Detection and Tracking in Infrared Images

摘要

The thesis deals with the detection and tracking of dim point targets in infrared images. Research topics include image process modeling with adaptive two-dimensional Least Mean Square (LMS) and Recursive Least Squares (RLS) prediction filters. Target detection is performed by significance testing the prediction error residual. A pulse tracker is developed which may be adjusted to discriminate target dynamics. The methods are applicable to detection and tracking in other spectral bands. (RH)