Suppression of atmospheric turbulence in video using an adaptive control grid interpolation approach

Atmospheric turbulence is a naturally occurring phenomenon that can severely limit the resolution of long distance optical and infrared sensors. Because atmospheric turbulence can degrade the appearance of video captured by these sensors, many of which are already deployed in the field, there is much interest in employing enhancement/restoration processing to improve data quality after acquisition. This paper presents a signal processing approach to suppressing atmospheric turbulence effects in sensor video using an adaptive control grid interpolation method. In this method, a dense dynamic motion vector field is derived from the characteristics of the atmospheric turbulence as seen in the data. The vector field is used in turn as part of the distortion compensation process, while preserving naturally occurring motion, such as that associated with the movement of objects within the stationary scene. The resulting algorithm is shown to produce enhanced video with quality significantly higher than that of the original