A temporal algorithm for IR small targets detection

Abstract

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.