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Optical 3D visualization under inclement weather conditions

In this paper, we propose an optical three-dimensional (3D) visualization under inclement weather conditions. These conditions include fog and night environments. For visualization under fog, we assume that fog is the unknown scattering media so that we use peplography technique which estimates the scattering media by Gaussian random process and detects ballistic photons from the scattering media by photon counting imaging. In addition, we use photon counting imaging with Bayesian estimation and adaptive statistical parameters for night vision. In this method, priori information of the scene can be assumed as Gamma distribution for calculation of posteriori distribution and adaptive statistical parameters can be calculated from the reconstructed 3D images. To obtain 3D information under inclement weather conditions, we use a passive 3D imaging technique such as integral imaging and computational reconstruction algorithm with 3D point cloud. Finally, we optimize these algorithms for real-time process and wearable devices. To support our proposed method, we implement preliminary experiments.