Spatio-temporal regularization for range imaging with high photon efficiency

Conventional depth imagers using time-of-flight methods collect hundreds to thousands of detected photons per pixel to form high-quality depth images of a scene. Through spatio-temporal regularization achieved with maximum a posteriori probability estimation under a scene prior and an inhomogeneous Poisson process likelihood function, we form depth images with dramatically higher photon efficiency-even as low as one detected photon per pixel. Simulations demonstrate the combination of high accuracy and high photon efficiency of our method, compared to the traditional maximum likelihood estimate of the depth image and other popular denoising algorithms.