Moving target detection in infrared imagery using a regularized CDWT optical flow

Abstract

A modified version of the CDWT optical flow algorithm developed by Magarey et al. is applied to the problem of moving target detection in noisy infrared image sequences. The optical flow algorithm is a hierarchical, phase-based approach. The modified version includes an explicit regularization of the motion field, which is of fundamental importance for the application in question. The data used consists of infrared imagery where pixel-size targets move in strongly cluttered backgrounds. To detect the targets different frames from the sequence are compared by subtraction of one from another. However, the motion of the sensor generates an apparent motion of the background across frames, and, as a consequence, the differences between background regions dominate the residue images. To avoid this effect, the estimated motion field between the frames is used to register the background spatially, so that only objects corresponding to potential targets appear in the residue images. Results of applying the method on 3 infrared image sequences are presented, which show that the target SNR is higher when the estimated motion field for the whole scene is explicitly regularized.