Turbulence conditions affect video images in two ways. It causes local blur, and it distorts the geometry of the scene. A video sequence of a still scene recorded under turbulence, appears to contain local random motion of small neighborhoods in the images. The blur is an accumulated result of the imaging point spread function and the local motion. The geometric distortion is due to the fact that small neighborhoods move in different directions. The restoration scheme reported here takes care of the geometric distortion as well as the blur. The geometric distortion is reduced by averaging the gray levels of relatively long (a few hundred images) video segments. The averaging reduces the geometric distortion, but it increases the blur. The second stage is the estimation of the global point spread function. The blur in the average image is a combination of the effects of the imaging system transfer function, the turbulence, and the averaging of the sequence. The global non-isotropic point spread function is estimated based on edge responses in the average image. A Wiener filter is used for the restoration of the image. The presented experimental results are superior to the results obtained by a previously proposed majority-vote technique.

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