Super-resolution enhancement of night vision image sequences

In several recent movie blockbusters, including Enemy of the State and Patriot Games, scientists magnify digital satellite imagery to determine the identities of people captured on surveillance video. These individuals appear rather blocky at the coarsest resolution scales due to undersampling by the image sensor array, but they become remarkably clear after zooming in on a particular region-of-interest. Obviously, real-world video enhancement algorithms are simply not capable of calculating the perfect results produced in Hollywood. However, additional detail can be extracted from an image sequence by integrating several adjacent digital video frames to compute a high-resolution video still. Extensive prior research has been conducted on the Bayesian super-resolution enhancement of visible light image sequences. For night vision applications, super-resolution enhancement must be applied to image sequences with frames acquired in the infrared region of the electromagnetic spectrum. Most of these applications are DoD-related (military), and they include the enhancement of infrared reconnaissance and surveillance imagery, as well as the enhancement of infrared imagery for automated target tracking and real time multisensor fusion. Several computational simulations have been performed, which visually depict how well the proposed technique enhances short night vision image sequences consisting of two-to-five frames This technique is capable of increasing resolution by factors up to 16×, although video stills appear somewhat blocky at higher magnification factors