Distorted IR target detection and tracking using composite filters

Abstract

The automatic target recognition (ATR), often time, is limited by the presence of background clutter and distortions such as scale, translation and rotation (both in-plane and out-of-plane) in both single and multi object cases. Such distortion invariant ATR and image understanding have been the subject of intense research in machine vision. In a previous work, we have demonstrated the usefulness of an amplitude-coupled minimum-average correlation energy (AC-MACE) filter in in-plane rotated SAR image ATR. The AC-MACE filter outperforms the regular MACE filter in rotation-related cases. Motion tracking is also an important task in computer vision, especially, when objects are subjected to certain viewing transformation. There are many problems in which very small objects undergoing motion must be detected and then tracked. For example, one of the most difficult goals of ATR is to spot incoming objects at long range, wherein the motion appears small and the signal to noise ratio (SNR) is poor. The system must be able to track such targets long enough to identify whether the object is a friend or foe. In this work, we are interested in locating both long-range and short-range moving objects in IR images wherein the object may vary from a few pixels in size to a large number of pixels in a sequence of IR images. The targets are submerged in background noise and clutter. Additionally, the tracking problem also involves out-of-plane rotation of the target. Thus, we investigate both MACE and AC-MACE filter for rotation and size invariant target detection and tracking using realistic IR images.