# Unraveling the paradox of intensity-dependent DVS pixel noise

arXiv: https://arxiv.org/abs/2109.08640 · HTML: https://mlsanity.com/paper/2109.08640/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Sep 2021.

## Built on by (most cited first, 16 of 16)

- [Spiking Neural Networks for Frame-based and Event-based Single Object Localization](https://mlsanity.com/paper/2206.06506/) (2022)
- [Event-based Background-Oriented Schlieren](https://mlsanity.com/paper/2311.00434/) (2023)
- [SoDaCam: Software-defined Cameras via Single-Photon Imaging](https://mlsanity.com/paper/2309.00066/) (2023)
- [Enhancing Visual Place Recognition via Fast and Slow Adaptive Biasing in Event Cameras](https://mlsanity.com/paper/2403.16425/) (2024)
- [Deblur e-NeRF: NeRF from Motion-Blurred Events under High-speed or Low-light Conditions](https://mlsanity.com/paper/2409.17988/) (2024)
- [From Sim-to-Real: Toward General Event-based Low-light Frame Interpolation with Per-scene Optimization](https://mlsanity.com/paper/2406.08090/) (2024)
- [Noise2Image: Noise-Enabled Static Scene Recovery for Event Cameras](https://mlsanity.com/paper/2404.01298/) (2024)
- [Long-Lived Accurate Keypoints in Event Streams](https://mlsanity.com/paper/2209.10385/) (2022)
- [Autobiasing Event Cameras](https://mlsanity.com/paper/2411.00729/) (2024)
- [On the Theory of Bias Tuning in Event Cameras](https://mlsanity.com/paper/2501.18788/) (2025)
- [Characterization of dim light response in DVS pixel: Discontinuity of event triggering time](https://mlsanity.com/paper/2404.17771/) (2024)
- [A Label-Free and Non-Monotonic Metric for Evaluating Denoising in Event Cameras](https://mlsanity.com/paper/2406.08909/) (2024)
- [Autobiasing Event Cameras for Flickering Mitigation](https://mlsanity.com/paper/2511.02180/) (2025)
- [Hybrid Event Frame Sensors: Modeling, Calibration, and Simulation](https://mlsanity.com/paper/2511.18037/) (2025)
- [NEC-Diff: Noise-Robust Event-RAW Complementary Diffusion for Seeing Motion in Extreme Darkness](https://mlsanity.com/paper/2603.20005/) (2026)
- [Event Cameras versus Frame Cameras for Synthetic-Aperture Imaging: A Simulation Study](https://mlsanity.com/paper/2610.20309/) (2026)

## Abstract (arXiv)

Dynamic vision sensor (DVS) event camera output is affected by noise, particularly in dim lighting conditions. A theory explaining how photon and electron noise affect DVS output events has so far not been developed. Moreover, there is no clear understanding of how DVS parameters and operating conditions affect noise. There is an apparent paradox between the real noise data observed from the DVS output and the reported noise measurements of the logarithmic photoreceptor. While measurements of the logarithmic photoreceptor predict that the photoreceptor is approximately a first-order system with RMS noise voltage independent of the photocurrent, DVS output shows higher noise event rates at low light intensity. This paper unravels this paradox by showing how the DVS photoreceptor is a second-order system, and the assumption that it is first-order is generally not reasonable. As we show, at higher photocurrents, the photoreceptor amplifier dominates the frequency response, causing a drop in RMS noise voltage and noise event rate. We bring light to the noise performance of the DVS photoreceptor by presenting a theoretical explanation supported by both transistor-level simulation results and chip measurements.