Video enhancement effectiveness for target detection

Michael Simon; Amber Fischer; Plamen Petrov

doi:10.1117/12.884137

25 May 2011 Video enhancement effectiveness for target detection

Michael Simon, Amber Fischer, Plamen Petrov

Proceedings Volume 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII; 80200W (2011) https://doi.org/10.1117/12.884137
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

Unmanned aerial vehicles (UAVs) capture real-time video data of military targets while keeping the warfighter at a safe distance. This keeps soldiers out of harm's way while they perform intelligence, surveillance and reconnaissance (ISR) and close-air support troops in contact (CAS-TIC) situations. The military also wants to use UAV video to achieve force multiplication. One method of achieving effective force multiplication involves fielding numerous UAVs with cameras and having multiple videos processed simultaneously by a single operator. However, monitoring multiple video streams is difficult for operators when the videos are of low quality. To address this challenge, we researched several promising video enhancement algorithms that focus on improving video quality. In this paper, we discuss our video enhancement suite and provide examples of video enhancement capabilities, focusing on stabilization, dehazing, and denoising. We provide results that show the effects of our enhancement algorithms on target detection and tracking algorithms. These results indicate that there is potential to assist the operator in identifying and tracking relevant targets with aided target recognition even on difficult video, increasing the force multiplier effect of UAVs. This work also forms the basis for human factors research into the effects of enhancement algorithms on ISR missions.

Citation Download Citation

Michael Simon, Amber Fischer, and Plamen Petrov "Video enhancement effectiveness for target detection", Proc. SPIE 8020, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VIII, 80200W (25 May 2011); https://doi.org/10.1117/12.884137

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KEYWORDS

Video

Video surveillance

Detection and tracking algorithms

Unmanned aerial vehicles

Denoising

Air contamination

Cameras

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