Learning to restore images degraded by atmospheric turbulence using uncertainty. (arXiv:2207.03447v1 [eess.IV])

Atmospheric turbulence can significantly degrade the quality of images
acquired by long-range imaging systems by causing spatially and temporally
random fluctuations in the index of refraction of the atmosphere. Variations in
the refractive index causes the captured images to be geometrically distorted
and blurry. Hence, it is important to compensate for the visual degradation in
images caused by atmospheric turbulence. In this paper, we propose a deep
learning-based approach for restring a single image degraded by atmospheric
turbulence. We make …

arxiv images learning restore uncertainty