Paper
15 June 2020 Ghost imaging for weak light imaging by using arrival time of photon and deep learning
Author Affiliations +
Abstract
This paper reports for high-sensitivity imaging based on Ghost imaging (GI), which is one of the single-pixel imaging. Although the GI is correlation-based imaging between structured illumination lights and detected signals, there is an advantage in detecting weak light intensity such as fluorescence of molecules. Especially, in the case of using extream weak light intensity, a photon signal is useful for imaging. Therefore, we focused on the arrival time of the first photon and used the time as the intensity of the signal. Furthermore, to improve the detection time, we applied machine learning to reduce the measurement number. In this paper, we have proposed the principle and some experimental results.
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Yasuhiro Mizutani, Shoma Kataoka, Tsutomu Uenohara, and Yasuhiro Takaya "Ghost imaging for weak light imaging by using arrival time of photon and deep learning", Proc. SPIE 11521, Biomedical Imaging and Sensing Conference 2020, 115210E (15 June 2020); https://doi.org/10.1117/12.2573239
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KEYWORDS
Signal detection

Machine learning

Sensors

Convolutional neural networks

Luminescence

Photodetectors

Convolution

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