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

ABSTRACT

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.

KEYWORDS:

• LIDAR
• photon counting
• 3D imaging
• signal processing

Acknowledgments

The authors thank Prof. Andrew M. Wallace for providing code from (21,22) and his precious advice.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

We would like to acknowledge financial support from the National Natural Science Foundation of China (NSFC) (61475191, 61875228), Natural Science Basic Research Plan in Shaanxi Province of China (2017ZDJC-27), and CAS Light of West China Program (XAB2015B24).