Image Super-Resolution for Improved Automatic Target Recognition

Abstract

Infrared imagers used to acquire data for automatic target recognition are inherently limited by the physical properties of their components. Fortunately, image super-resolution techniques can be applied to overcome the limits of these imaging systems. This increase in resolution can have potentially dramatic consequences for improved automatic target recognition (ATR) on the resultant higher-resolution images. We will discuss super-resolution techniques in general and specifically review the details of one such algorithm from the literature suited to real-time application on forward-looking infrared (FLIR) images. Following this tutorial, a numerical analysis of the algorithm applied to synthetic IR data will be presented, and we will conclude by discussing the implications of the analysis for improved ATR accuracy.