Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging
Traditional cameras face a trade-off between low-light performance and high-speed imaging: longer exposure times to capture sufficient light results in motion blur, whereas shorter exposures result in Poisson-corrupted noisy images. While burst photography techniques help mitigate this tradeoff, conventional cameras are fundamentally limited in their sensor noise characteristics. Event cameras and single-photon avalanche diode (SPAD) sensors have emerged as promising alternatives to conventional cameras due to their desirable properties. SPADs are capable of single-photon sensitivity with microsecond temporal resolution, and event cameras can measure brightness changes up to 1 MHz with low bandwidth requirements. We show that these properties are complementary, and can help achieve low-light, high-speed image reconstruction with low bandwidth requirements. We introduce a sensor fusion framework to combine SPADs with event cameras to improve the reconstruction of high-speed, low-light scenes while reducing the high bandwidth cost associated with using every SPAD frame. Our evaluation, on both synthetic and real sensor data, demonstrates significant enhancements ($> 5$>5 dB PSNR) in reconstructing low-light scenes at high temporal resolution (100 kHz) compared to conventional cameras. Event-SPAD fusion shows great promise for real-world applications, such as robotics or medical imaging.
Authors
- Edoardo Charbon (ORCID: https://orcid.org/0000-0002-0620-3365)
- Siddharth Somasundaram (ORCID: https://orcid.org/0000-0002-6850-9968)
- Davide Scaramuzza (ORCID: https://orcid.org/0000-0002-3831-6778)
- Akshat Dave (ORCID: https://orcid.org/0000-0003-0560-632X)
- Manasi Muglikar (ORCID: https://orcid.org/0000-0002-5091-1860)
- Ramesh Raskar
Institutions
- University of Zurich (CH)
- IIT@MIT (US)
- École Polytechnique Fédérale de Lausanne (CH)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2025-06-19
- DOI
- https://doi.org/10.1109/tpami.2025.3576698
- Citations
- 3
- Primary Topic
- Advanced Optical Sensing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 3.58