Plenoptic Imaging for Seeing Through Turbulence

Atmospheric distortion is one of the main barriers to imaging over long distances. Changes in the local refractive index perturb light rays as they pass through, causing distortion in the images captured in a camera. This problem can be overcome to some extent by using a plenoptic imaging system (one which contains an array of microlenses in the optical path). In this paper, we propose a model of image distortion in the microlens images and propose a computational method for correcting the distortion. This algorithm estimates the distortion field in the microlenses. We then propose a second algorithm to infer a consistent final image from the multiple images of each pixel in the microlens array. These algorithms detect the distortion caused by changes in atmospheric refractive index and allow the reconstruction of a stable image even under turbulent imaging conditions. Finally we present some reconstruction results and examine whether there is any increase in performance from the camera system. We demonstrate that the system can detect and track distortions caused by turbulence and reconstruct an improved final image.