What Does a One-Bit Quanta Image Sensor Offer?
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Abstract (arXiv)
The one-bit quanta image sensor (QIS) is a photon-counting device that captures image intensities using binary bits. Assuming that the analog voltage generated at the floating diffusion of the photodiode follows a Poisson-Gaussian distribution, the sensor produces either a ``1'' if the voltage is above a certain threshold or ``0'' if it is below the threshold. The concept of this binary sensor has been proposed for more than a decade, and physical devices have been built to realize the concept. However, what benefits does a one-bit QIS offer compared to a conventional multi-bit CMOS image sensor? Besides the known empirical results, are there theoretical proofs to support these findings? The goal of this paper is to provide new theoretical support from a signal processing perspective. In particular, it is theoretically found that the sensor can offer three benefits: (1) Low-light: One-bit QIS performs better at low-light because it has a low read noise, and its one-bit quantization can produce an error-free measurement. However, this requires the exposure time to be appropriately configured. (2) Frame rate: One-bit sensors can operate at a much higher speed because a response is generated as soon as a photon is detected. However, in the presence of read noise, there exists an optimal frame rate beyond which the performance will degrade. A Closed-form expression of the optimal frame rate is derived. (3) Dynamic range: One-bit QIS offers a higher dynamic range. The benefit is brought by two complementary characteristics of the sensor: nonlinearity and exposure bracketing. The decoupling of the two factors is theoretically proved, and closed-form expressions are derived.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Aug 2022.
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Citing papers per year: 2022: 1; 2023: 4; 2024: 5; 2025: 0; 2026: 1.
11 papers.
- 2023HDR Imaging with Spatially Varying Signal-to-Noise Ratioscited by 8
- 2023Spatially Varying Exposure with 2-by-2 Multiplexing: Optimality and Universalitycited by 6
- 2024CT-Bound: Robust Boundary Detection From Noisy Images Via Hybrid Convolution and Transformer Neural Networkscited by 3
- 2024Quanta Video Restorationcited by 3
- 2024bit2bit: 1-bit quanta video reconstruction via self-supervised photon predictioncited by 2
- 2024Generative Quanta Color Imagingcited by 1
- 2024Photon Inhibition for Energy-Efficient Single-Photon Imagingcited by 1
- 2022StereoISP: Rethinking Image Signal Processing for Dual Camera Systemscited by 0
- 2023The impact of frame quantization on the dynamic range of a one-bit image sensorcited by 0
- 2023eRPCA: Robust Principal Component Analysis for Exponential Family Distributionscited by 0
- 2026Fundamental Recovery Bounds for SPAD Signals under Stationary Fluxcited by 0
- 2026Fundamental Recovery Bounds for SPAD Signals under Stationary Flux12 Jan 2026
- 2024bit2bit: 1-bit quanta video reconstruction via self-supervised photon prediction30 Oct 2024
- 2024Quanta Video Restoration19 Oct 2024
- 2024Photon Inhibition for Energy-Efficient Single-Photon Imaging26 Sep 2024
- 2024Generative Quanta Color Imaging28 Mar 2024
- 2024CT-Bound: Robust Boundary Detection From Noisy Images Via Hybrid Convolution and Transformer Neural Networks25 Mar 2024
- 2023eRPCA: Robust Principal Component Analysis for Exponential Family Distributions30 Oct 2023
- 2023Spatially Varying Exposure with 2-by-2 Multiplexing: Optimality and Universality30 Jun 2023
- 2023HDR Imaging with Spatially Varying Signal-to-Noise Ratios30 Mar 2023
- 2023The impact of frame quantization on the dynamic range of a one-bit image sensor2 Feb 2023
- 2022StereoISP: Rethinking Image Signal Processing for Dual Camera Systems11 Nov 2022
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Close in wording, no citation either way
- 2022On the Insensitivity of Bit Density to Read Noise in One-bit Quanta Image Sensors
- 2021Differential Deep Detection in Massive MIMO With One-Bit ADC
- 2026Quantum Gradient-Based Approach for Edge and Corner Detection Using Sobel Kernels
- 2023HDR Imaging With One-Bit Quantization
- 2026Design Environment of Quantization-Aware Edge AI Hardware for Few-Shot Learning
- 2024One-Bit MIMO Detection: From Global Maximum-Likelihood Detector to Amplitude Retrieval Approach ↗
- 2026One Qubit Can Beat One Bit: Quantum Advantage for Post-Training Quantization
- 2024Variable Resolution Pixel Quantization for Low Power Machine Vision Application on Edge