Image Enhancement and Machine Learning for Improving Man-Portable Targeting Systems

Modern DoD applications are benefiting from the proliferation of EO/IR sensor technology. As imagers become cheaper and smaller, they are being more widely deployed for a variety of scenarios. This trend is exemplified by the Navys Future Targeting System (FTS), which will provide laser designation, laser spot imaging, and some target location functions in a single 5.5-pound unit, replacing discrete laser designators (28 pounds) and laser spot imagers (7 pounds). This new system will offer a single compact system for performing rapid target acquisition, laser terminal guidance operations, and laser spot imaging to USMC troops responsible for supporting arms observers, spotters, and controllers. However, a significant burden is still placed on the operator. In this project, we will develop image processing technology to improve operator effectiveness by enhancing the imagery collected by the FTS and other similar sensors, as well as integrate automated techniques for detecting and classifying objects of interest in the collected video streams.