Evaluation of forward-looking infrared sensors for automatic target recognition using an information-theoretic approach

The development of an information-theoretic image measure for sensor evaluation, under contract to the United States Air Force, is described. Although current approaches are based on human perception models, a need exists for evaluation of sensors for automatic target cuing/automatic target recognition (ATC/ATR) systems. Such an evaluation should be performed in terms of the probabilities of detection/identification and false alarms, independent of the idiosyncrasies of the specific ATC/ATR algorithms. Such an approach based on the information-theoretic content of images for the target versus background separability is being developed and applied to evaluating sensors using the tower test data collected at the Wright Laboratories.