Time series processing of FLIR imagery for MTI and change detection

The paper addresses the problem of calibrating FLIR images of a scene that are acquired at different time points to construct information for moving target indication (MTI) and change detection. A signal model is developed to identify variations and imperfections of an FLIR sensor in time. This model is utilized to compensate for relatively slow variations of a bias in the FLIR sensor via a Fourier-based processing. Furthermore, a two-dimensional adaptive filtering method is developed to compensate for variations of the image point response (IPR) of a FLIR sensor as well as sub-pixel changes in the relative coordinates of the sensor-target over time. Results with time series FLIR, data of a scene with an airborne helicopter and a ground target are provided.