Sequences pattern effects on the time and space united coding single photon counting imaging method

Shanshan Shen

doi:10.1117/12.3047773

13 December 2024 Sequences pattern effects on the time and space united coding single photon counting imaging method

Shanshan Shen

Proceedings Volume 13501, AOPC 2024: Computational Imaging Technology; 135010B (2024) https://doi.org/10.1117/12.3047773
Event: Applied Optics and Photonics China 2024 (AOPC2024), 2024, Beijing, China

Abstract

In this paper, we study the sequences pattern effects on a new imaging architecture for unambiguous ranging by combining the advantages of space coding based single-pixel imaging technology and spread spectrum time coding based scanning imaging technology. We firstly derive the time-space united correlation nonlinear detection model based on single photon detection.The depth image is restored by convex optimization inversion algorithm.Then we introduce the arm probability of steady response model to the signal-to-noise ratio model. The relationship of SNR and the 1-bit ratio in bitstream with different dead time by Monte Carlo simulation is studied. The simulation test results show that with the ratio of randomly distributed 1-bits in transmitted sequences pattern increased, the system SNR gets better first and then gets worse. Best pattern of transmitted bit stream according to different dead time leads to the best SNR. Theory model is almost consistent with Monte Carlo simulation. Theoretical model and simulation test both prove that, compared to the conventional space coding based single-pixel imaging technology, this approach enhances scene reconstruction quality with depth accuracy improvements of 9 using 0.18 1-bit ratio sequences with 80ns deadtime. The proposed imaging architecture may provide a new path for improved non-scanning lidar systems.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shanshan Shen "Sequences pattern effects on the time and space united coding single photon counting imaging method", Proc. SPIE 13501, AOPC 2024: Computational Imaging Technology, 135010B (13 December 2024); https://doi.org/10.1117/12.3047773

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KEYWORDS

Signal to noise ratio

Image restoration

Photon counting

LIDAR

Digital micromirror devices

Imaging systems

Depth maps

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