Paint target detection in IR image sequences: a hypothesis-testing approach based on target and clutter temporal profile modeling

We approach the problem of point target detection in infrared image sequenc es by modeling the temporal behavior of clutter and targets on a single-pix el basis. These models, which are experimentally verified, are then used to develop a temporal likelihood-ratio test and derive the corresponding deci sion rule. We demonstrate the effectiveness of the technique by applying it to real infrared image sequences containing targets of opportunity and evo lving cloud clutter. The physical models and resulting hypothesis-testing a pproach could also be applicable to other image-sequence-processing scenari os, using acquisition systems besides infrared imaging, such as the detecti on of small moving objects or structures in a biomedical or biological imag ing scenario, or the detection of satellites, meteors, or other celestial b odies in night-sky imagery acquired using a telescope. (C) 2000 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(00)03108-1].