Modulation Domain Features for Discriminating Infrared Targets and Backgrounds

For the first time, we compute modulation domain features for infrared targets and backgrounds, including dominant modulations that characterize the local texture contrast, orientation, and granularity. We present a practical computational approach and introduce a new FM algorithm designed to reduce the approximation errors characteristic of many existing discrete techniques. By performing experiments against actual FLIR approach sequences, we verify that typical IR imagery does indeed possess sufficient texture structure for effective modulation domain characterization. We demonstrate qualitatively that the modulation domain features can significantly enhance target-background class separability relative to pixel domain features.