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.
Benefit: The technology developed in this project will reduce operator burden and improve overall effectiveness by enhancing videos produced by imagers, such as the new FTS, and providing cuing and classification information to the user. The image processing techniques developed in this project will be integrated directly into the FTS and provided as a standalone, streaming box capable of working with other sensor platforms. In either form, our technology will enhance the incoming video stream and analyze it to provide additional information to the user.
Keywords: video processing, video processing, Image Processing, Long Range, detection, Machine Learning, Analytics, identification, Image Enhancement
