Evaluation of FLIR sensors for automatic target recognition using an information-theoretic approach

This paper describes the development of an information-theoretic image measure for sensor evaluation under the contract to the United States Air Force. While current approaches are based on human perception models, a need exists for evaluation of sensors for 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 vs. background separability is being developed and applied to evaluating sensors using the Tower Test data collected at the Wright Laboratories