Dim point target tracking in infrared image sequences with low SNR

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2016
Güler, Zahide Selin
Dim point target tracking in infrared (IR) images has been an active research area especially in military fields. Due to the long distance from IR sensors, target appears as a dim moving point hidden in a heavily cluttered background and causes the Signal to Noise Ratio (SNR) to be very low. We present a tracking algorithm based on Particle Filters (PF), which estimates the target position by using both brightness level and motion model measurements. A target candidate list for the presented PF algorithm is generated by Top-Hat background subtraction and statistical information of frame sequences. An important advantage of the proposed algorithm is that it does not use any a priori knowledge of the target properties. The performance of the proposed algorithm is evaluated on different types of IR image sequences generated from different detector types, varying SNR levels and different target motions. The experimental results demonstrate that the algorithm can successfully track dim moving point target in low SNR environment and accurately estimate its trajectory.

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Citation Formats
Z. S. Güler, “Dim point target tracking in infrared image sequences with low SNR,” M.S. - Master of Science, Middle East Technical University, 2016.