Sub-picosecond photon-efficient 3D imaging using single-photon sensors

TL;DR

This paper introduces a probabilistic model and inverse algorithms for single-photon sensors that significantly improve timing accuracy and enable practical sub-picosecond 3D imaging with high photon efficiency.

Contribution

It develops a novel probabilistic model to correct pileup distortions and presents inverse methods for accurate scene depth and reflectance estimation in photon-limited conditions.

Findings

Over an order of magnitude improvement in timing accuracy.

First demonstration of sub-picosecond photon-efficient 3D imaging.

Effective in scenarios with widely-varying photon counts.

Abstract

Active 3D imaging systems have broad applications across disciplines, including biological imaging, remote sensing and robotics. Applications in these domains require fast acquisition times, high timing resolution, and high detection sensitivity. Single-photon avalanche diodes (SPADs) have emerged as one of the most promising detector technologies to achieve all of these requirements. However, these detectors are plagued by measurement distortions known as pileup, which fundamentally limit their precision. In this work, we develop a probabilistic image formation model that accurately models pileup. We devise inverse methods to efficiently and robustly estimate scene depth and reflectance from recorded photon counts using the proposed model along with statistical priors. With this algorithm, we not only demonstrate improvements to timing accuracy by more than an order of magnitude compared to the state-of-the-art, but this approach is also the first to facilitate sub-picosecond-accurate, photon-efficient 3D imaging in practical scenarios where widely-varying photon counts are observed.