Single-Photon LiDAR for Real-Time Underwater Target Detection and 3D Video Reconstruction

Single-photon systems are emerging as a key approach to 3D Imaging. In this talk I introduce a two-step statistical based approach for real-time image reconstruction applicable to a transmission medium with extreme light scattering conditions. The first step is optional and involves a target detection method to select informative pixels which have photons reflected from the target. The second is a reconstruction algorithm that exploits data statistics and multiscale information to deliver clean depth and reflectivity images together with associated uncertainty maps. Both methods involve independent operations that have been implemented in parallel on graphics processing units (GPUs), which enables real-time data processing of moving scenes at more than 50 depth frames per second for an image of 128x128 pixels. Comparisons with state-of-the-art algorithms on simulated and real underwater data demonstrate the benefit of the proposed framework for target detection, and for fast and robust depth estimation at multiple frames per second.