In order to detect small dim targets in IR image sequences, a temporal processing technique is investigated. Based on the
temporal difference models for background noise pixel, target pixel and clutter pixel, we formulate the detection problem
in 2 steps, Cross Correlation Target Detection method (CCTD) and Generalized Likelihood Ratio Test (GLRT). After
CCTD step, noise pixels in the image sequences are almost suppressed and only target pixels and a few clutter pixels can
pass the detection threshold. In order to further the targets detection in these pixels, an improved GLRT method is
developed. This improved GLRT method can suppress the clutter pixels sequentially and enhance the performance of the
temporal detection method. Theoretical analyses show that this algorithm can detect targets on very high detection
probability and very low false alarm probability. The effectiveness of the technique is demonstrated by applying it to real
world infrared image sequences containing cloud clutter and airplanes flying at long range.
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