Optical correlation filter fusion for object detection

We consider the detection of candidate objects (regions of interest) in a scene containing high clutter, multiple objects in different classes, independent of aspect view, with hot, cold, bimodal, and partial object variations and with high and low contrast targets. We use three different filters with each designed to produce high probability of detection (PD). We fuse the results from different outputs to reduce the probability of false alarms (PFA). All filters are realizable on an optical correlator.