IR system field performance with superresolution

Abstract

Superresolution processing is currently being used to improve the performance of infrared imagers through an increase in sampling, the removal of aliasing, and the reduction of fixed-pattern noise. The performance improvement of superresolution has not been previously tested on military targets. This paper presents the results of human perception experiments to determine field performance on the NVESD standard military eight (8)-target set using a prototype LWIR camera. These experiments test and compare human performance of both still images and movie clips, each generated with and without superresolution processing. Lockheed Martin's XR® algorithm is tested as a specific example of a modern combined superresolution and image processing algorithm. Basic superresolution with no additional processing is tested to help determine the benefit of separate processes. The superresolution processing is modeled in NVThermIP for comparison to the perception test. The measured range to 70% probability of identification using XR® is increased by approximately 34% while the 50% range is increased by approximately 19% for this camera. A comparison case is modeled using a more undersampled commercial MWIR sensor that predicts a 45% increase in range performance from superresolution.