# Photon-Flooded Single-Photon 3D Cameras

arXiv: https://arxiv.org/abs/1903.08347 · HTML: https://mlsanity.com/paper/1903.08347/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Mar 2019.

## Built on by (most cited first, 23 of 23)

- [Towards 3D Vision with Low-Cost Single-Photon Cameras](https://mlsanity.com/paper/2403.17801/) (2024)
- [Photon-Starved Scene Inference using Single Photon Cameras](https://mlsanity.com/paper/2107.11001/) (2021)
- [Adaptive Gating for Single-Photon 3D Imaging](https://mlsanity.com/paper/2111.15047/) (2021)
- [Count-Free Single-Photon 3D Imaging with Race Logic](https://mlsanity.com/paper/2307.04924/) (2023)
- [Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms](https://mlsanity.com/paper/2308.13473/) (2023)
- [Resolution Limit of Single-Photon LiDAR](https://mlsanity.com/paper/2403.17719/) (2024)
- [Using a Distance Sensor to Detect Deviations in a Planar Surface](https://mlsanity.com/paper/2408.03838/) (2024)
- [Single-Photon 3D Imaging with Equi-Depth Photon Histograms](https://mlsanity.com/paper/2408.16150/) (2024)
- [Quanta Video Restoration](https://mlsanity.com/paper/2410.14994/) (2024)
- [Recovering Parametric Scenes from Very Few Time-of-Flight Pixels](https://mlsanity.com/paper/2509.16132/) (2025)
- [Swept-Angle Synthetic Wavelength Interferometry](https://mlsanity.com/paper/2205.10655/) (2022)
- [Passive Micron-scale Time-of-Flight with Sunlight Interferometry](https://mlsanity.com/paper/2211.10732/) (2022)
- [Generative Quanta Color Imaging](https://mlsanity.com/paper/2403.19066/) (2024)
- [Centimeter-Wave Free-Space Time-of-Flight Imaging](https://mlsanity.com/paper/2105.11606/) (2021)
- [Onsite Non-Line-of-Sight Imaging via Online Calibrations](https://mlsanity.com/paper/2112.14555/) (2021)
- [Simulating single-photon detector array sensors for depth imaging](https://mlsanity.com/paper/2210.05644/) (2022)
- [Joint Depth and Reflectivity Estimation using Single-Photon LiDAR](https://mlsanity.com/paper/2505.13250/) (2025)
- [3D Reconstruction from Transient Measurements with Time-Resolved Transformer](https://mlsanity.com/paper/2510.09205/) (2025)
- [Hardware-aware Coding Function Design for Compressive Single-Photon 3D Cameras](https://mlsanity.com/paper/2510.12123/) (2025)
- [Fundamental Recovery Bounds for SPAD Signals under Stationary Flux](https://mlsanity.com/paper/2601.07599/) (2026)
- [Ghosts in the Point Clouds: De-glaring LiDAR in the Transient Domain](https://mlsanity.com/paper/2605.24753/) (2026)
- [Learning to Suppress SPAD-based LiDAR Flare](https://mlsanity.com/paper/2607.03247/) (2026)
- [High-Flux Count-Free Single-Photon 3D Cameras](https://mlsanity.com/paper/2608.18306/) (2026)

## Abstract (arXiv)

Single photon avalanche diodes (SPADs) are starting to play a pivotal role in the development of photon-efficient, long-range LiDAR systems. However, due to non-linearities in their image formation model, a high photon flux (e.g., due to strong sunlight) leads to distortion of the incident temporal waveform, and potentially, large depth errors. Operating SPADs in low flux regimes can mitigate these distortions, but, often requires attenuating the signal and thus, results in low signal-to-noise ratio. In this paper, we address the following basic question: what is the optimal photon flux that a SPAD-based LiDAR should be operated in? We derive a closed form expression for the optimal flux, which is quasi-depth-invariant, and depends on the ambient light strength. The optimal flux is lower than what a SPAD typically measures in real world scenarios, but surprisingly, considerably higher than what is conventionally suggested for avoiding distortions. We propose a simple, adaptive approach for achieving the optimal flux by attenuating incident flux based on an estimate of ambient light strength. Using extensive simulations and a hardware prototype, we show that the optimal flux criterion holds for several depth estimators, under a wide range of illumination conditions.