Fernando Mujica Clark Atlanta Univ. (United States) Romain Murenzi Clark-Atlanta Univ. (United States) Mark J. T. Smith Georgia Institute of Technology (United States) Jean-Pierre Leduc Clark Atlanta Univ. (United States)
Accurate object tracking is important in defense applications where an interceptor missile must hone into a target and track it through the pursuit until the strike occurs. The expense associated with an interceptor missile can be reduced through a distributed processing arrangement where the computing platform on which the tracking algorithm is run resides on the ground, and the interceptor need only carry the sensor and communications equipment as part of its electronics complement. In this arrangement, the sensor images are compressed, transmitted to the ground, and decompressed to facilitate real-time downloading of the data over available bandlimited channels. The tracking algorithm is run on a ground-based computer while tracking results are transmitted back to the interceptor as soon as they become available. Compression and transmission in this scenario introduce distortion. If severe, these distortions can lead to erroneous tracking results. As a consequence, tracking algorithms employed for this purpose must be robust to compression distortions. In this paper we introduced a robust object tracking algorithm based on the continuous wavelet
transform. The algorithm processes image sequence data on a frame-by-frame basis, implicitly taking advantage of temporal history and spatial frame filtering to reduce the impact of compression artifacts. Test results show that tracking performance can be maintained at low transmission bit rates and can be used reliably in conjunction with many well-known image compression algorithms.