Performance analysis of different pixel-wise processing methods for depth imaging with single photon detection data

We establish a long-range single photon counting three-dimensional (3D) imaging system based on cage optical structure. Five different pixel-wise processing methods for time-of-flight (TOF) photon counting data are compared with data collected by our 3D imaging system for ranges 40-700 m and a suita...

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Bibliographic Details
Published in:Journal of modern optics 2019-05, Vol.66 (9), p.976-985
Main Authors: Kang, Yan, Li, Lifei, Li, Dongjian, Liu, Dawei, Zhang, Tongyi, Zhao, Wei
Format: Article
Language:English
Subjects:
3D imaging
Computer simulation
Counting
Cross correlation
Image quality
LIDAR
Markov analysis
Markov chains
photon counting
Photons
Pixels
Response functions
signal processing
Three dimensional imaging
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Summary:We establish a long-range single photon counting three-dimensional (3D) imaging system based on cage optical structure. Five different pixel-wise processing methods for time-of-flight (TOF) photon counting data are compared with data collected by our 3D imaging system for ranges 40-700 m and a suitable representation model for photon counting data is proposed for pixel-wise processing. Experimental results show that these methods exploit the instrumental response function (IRF), yielding a high-quality 3D image. When the signal photon counts are greater than 13 per pixel, the resulting mean absolute error (MAE) values of the IRF-based methods are better than results from the non-IRF-based methods. Regarding IRF-based methods, the union of subspace (UOS) model-based approach and cross correlation are more suitable than the Markov chain Monte Carlo (MCMC) method in the condition of a small number of return signal photons. These results offer valuable information to promote the implementation of photon counting 3D imaging in real applications.
ISSN:0950-0340
1362-3044
DOI:10.1080/09500340.2019.1596322