Automatic detection of small objects from their infrared state-of-polarization vectors

A technique for automatic detection of targets from their infrared signature's state-of-polarization vector is described. The bounds on the Bayesian total probability of errors are estimated from the observed Stokes vector imagery and used as metrics for separating targets from background clutter. The performance of the proposed approach for objects under various geometries is studied in terms of receiver operating characteristic curves. The new results, which have been obtained from data from the U.S. Air Force's Infrared Modeling and Analysis polarimetric infrared simulation tool, indicate the usefulness of polarimetric infrared signatures for the automatic detection of small targets.