Point target detection in IR image sequences based on target and clutter temporal profile modeling

Abstract

In this paper, we approach the problem of point target detection in IR image sequences by modeling the temporal behavior of clutter and targets on a single pixel basis. These models, which are experimentally verified, are then used to develop a temporal likelihood ratio test and drive the corresponding decision rule. We demonstrate the effectiveness of the technique by applying it to real IR image sequences containing targets of opportunity and evolving cloud clutter. The physical models and resulting hypothesis testing approach could also be applicable to other image sequence processing scenarios. Using acquisition system besides IR imaging, such as detection of small moving objects or structures in a biomedical or biological imaging scenario, or the detection of satellites, meteors or other celestial bodies in night sky imagery acquired using a telescope.