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When observing a scene horizontally at a long distance in the near-infrared domain, degradations due
to atmospheric turbulence often occur. In our previous work, we presented two hybrid methods to restore
videos degraded by such local perturbations. These restoration algorithms take advantages of a space-time
Wiener filter and a space-time regularization by the Laplacian operator. Wiener and Laplacian regularization
results are mixed differently depending on the distance between the current pixel and the nearest edge point.
It was shown that a gradation betweenWiener and Laplacian areas improves results quality, so that only the
algorithm using a gradation will be used in this article.
In spite of a significant improvement in the obtained images quality, our restoration results greatly depend
on the segmentation image used in the video processing. We then propose a method to select automatically
the best segmentation image
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