As warfare moves into a new era, military strategists tool up with unmanned aircraft systems (UAS) or drones to provide the visual surveillance the new combat environment requires. In urban warfare, where counterinsurgency and counterterrorist missions typically occur, troops rely on the Intelligence, Surveillance, and Reconnaissance (ISR) forces for persistent air surveillance, precision air strikes, and swift airlift support. ISR forces are able to sweep wide areas, detect activity, stare at key places for hours and days at a time, and complete a targeting cycle in minutes.

The reconnaissance capabilities of the forward camera on the Predator and Reaper, known as the “MTS Ball” or MQ-16 electro-optical/infrared camera, can read a driver’s license from 20,000+ feet.

Robotics, and in particular the UASs, are changing the nature of warfighting. Unmanned aircraft systems are also referred to as drones or unmanned aerial vehicles (UAV). They are called remotely piloted aircraft (RPA) by the U.S. Air Force. The UASs can transmit a direct feed to a nearby ground control station or broadcast via satellite to command centers around the globe.

The key enabling technology responsible for the breakthrough capabilities of the UAS and the subsequent transformation of warfare is Full-Motion Video (FMV). FMV provides an on-demand, close-up view of the combat zone that would not otherwise be possible. It enables commanders to make decisions and execute missions from a safe distance without endangering the lives of their troops. Practically speaking, without FMV from the aircraft’s onboard cameras, pilots would not be able to navigate the drone remotely from the ground.

Full-motion video adds a fourth dimension to imagery: the ability to track activity over time. FMV provides outstanding event fidelity, seamless event progression, and a full context regarding the nature of the location and activities being viewed.

Exploiting the full benefits that FMV has to offer requires overcoming some challenges. First, the bandwidth requirements for broadcasting FMV, especially in high definition (HD), are tremendous. Second, the amount of digital storage space needed to retain the sheer volume of FMV from missions is staggering. Third, the human effort involved in viewing, analyzing, and disseminating the footage is overwhelming. Fourth, and most importantly, the quality and clarity of the captured images is often so poor that targets cannot be clearly identified.

Current FMV Image Quality Inconsistent

Producing high-quality imagery on a mobile platform such as the UAS poses some interesting challenges due to its motion and the resulting image perspectives. The quality of the video imagery can be compromised by narrow camera field-of-view, datalink degradations, poor environmental conditions (e.g., dawn/dusk/night, adverse weather, variable clouds), bandwidth limitations, or a highly cluttered visual scene (e.g., in urban areas or mountainous terrain).

Given the weight of these issues, the emergence of a new solution would be welcome. Fortunately, recent technology advances now make it possible to significantly enhance the image quality of FMV in real time and address these pressing problems. A variety of sophisticated image enhancement algorithms that have successfully been used on still images can now be applied to FMV. Image processing algorithms are computationally intensive, especially for FMV. Multiple video streams at 30 frames per second in real time, with zero latency, must be processed. The only way to do this is with an advanced platform capable of high-power parallel processing. A commercial off-the-shelf (COTS) platform that uses open architecture algorithms to enhance FMV image quality in real time is now available. This platform is designed to meet the requirements for applications such as the drone, and can accommodate multiple video input streams and route them to any combination of attached displays or network connections.

« Start Prev 1 2 3 Next End»

White Papers

Computer Aided Design of Suspension Mechanisms
Sponsored by Dr. C H Suh
Algorithms for Change Point Analysis
Sponsored by Numerical Algorithms Group
Using UV LEDs to Cure Fiber Optic Cables
Sponsored by Excelitas
Beyond Telematics: IoT
Sponsored by Bsquare
Minimum Incremental Motion and Holding Stability in Beamline Positioning
Sponsored by Aerotech
Evaluating Electrically Insulating Epoxies
Sponsored by Master Bond

White Papers Sponsored By:

The U.S. Government does not endorse any commercial product, process, or activity identified on this web site.