Mr. Shuichi Namiki Profile

Shuichi Namiki

at Tokyo Univ of Science

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Proceedings Article | 1 May 2022 Paper

Imaging method using multi-threshold pattern for photon detection of quanta image sensor

Shuichi Namiki, Shunichi Sato, Yusuke Kameda, Takayuki Hamamoto

Proceedings Volume 12177, 1217702 (2022) https://doi.org/10.1117/12.2625974

KEYWORDS: Signal to noise ratio, Image sensors, Photodetectors, Denoising, Image processing, Edge detection, Image quality, Temporal resolution, Statistical analysis, Sensors

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In recent years, the development of quanta image sensor (QIS), which can observe the amount of incident light intensity in units of photons, has been progressing. In QIS imaging, a large number of photon incident observations are performed in spatiotemporal direction, and multivalued images are obtained by reconstruction processing. In this observation, the binary value is output according to whether the number of incident photons exceeds a certain natural number of threshold preset in the minute photon detector (jot). In many existing methods for QIS imaging, a uniform threshold is set for all jots, the reconstructed multivalued image may be overexposed or underexposed. On the other hand, the method of setting an optimal threshold for each local region according to the scene requires time for adjustment, which leads to a decrease in temporal resolution. In this paper, we propose an imaging method that always accurately captures a wide range of light intensity from low to high by introducing a periodic pattern consisting of multiple thresholds. Since we do not adjust the threshold according to the scene, we can fundamentally avoid the degradation of temporal resolution. In addition, since the threshold applied to jots has a variety of values, it is possible to acquire a high-quality multivalued image even with a small number of photon incident observations. Our proposed method consists of three components: multivalued image reconstruction and noise reduction taking into account the characteristics of photon incident observation, and optimization of the periodic pattern.

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