Dr. Ling Ye Profile

Dr. Ling Ye

at Nanjing Univ of Science and Technology

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Publications (2)

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Proceedings Article | 18 September 2018 Paper

A photon-efficient method based on curve fitting for photon counting 3D imaging lidar

Ling Ye, Guohua Gu, Weiji He, Wenye Yin, Jie Lin, Jian Fang

Proceedings Volume 10767, 107670X (2018) https://doi.org/10.1117/12.2317805

KEYWORDS: LIDAR, Photon counting, Avalanche photodiodes, 3D image processing, Photodetectors, Quantitative analysis, Single photon detectors, Atmospheric optics

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Time-of-flight (TOF) Lidar is widely used in capturing three-dimensional (3D) structure and reflectivity information. For using Geiger-mode avalanche photodiode (Gm-APD) and the technique time correlated single photon counting (TCSPC), a direct-detection 3D imaging lidar has high sensitivity in low-light-level (LLL) scene. Traditional method needs long fixed dwell time to collect tens of thousands of photons to find accurate range and mitigate Poisson noise at each pixel. We present a method that acquires accurate depth and intensity images using a small amount of detected echo photons and having quantitative analysis to estimate whether results are in the confidence interval. Based on prior knowledge that the echo signal is in the shape of emitted laser, we use one or two orders of magnitude back-reflected photons less than traditional method, fitting a curve of laser-return pulse by nonlinear least-squares fitting in order to obtain the range. The condition of moving to next pixel in our method is acquiring a fixed number of back-reflected photons, instead of sampling for a fixed time. This adaptive jump condition is able to speed up the scanning without more distortion. The results are analyzed with chi-square test to determine if the curve we fit has enough credibility. This quantitative analysis provides an important judgment condition for our method of fitting curve to recover the depth image. Experimental results demonstrate that our method is able to obtain the millimeter accuracy depth image in the confidence interval using hundreds of photons and increases photon-efficiency more than 10-fold over traditional method. Thus our method will be useful in LLL scene, such as military reconnaissance and remote sensing.

Proceedings Article | 6 September 2017 Paper

Adaptive compressed photon counting 3D imaging based on wavelet trees and Hadamard multiplexing

Huidong Dai, Guohua Gu, Weiji He, Ling Ye, Tianyi Mao, Qian Chen

Proceedings Volume 10410, 104101A (2017) https://doi.org/10.1117/12.2272923

KEYWORDS: Photon counting, 3D acquisition, Wavelets, Multiplexing, 3D metrology, Image acquisition

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A photon counting 3D imaging system with short-pulsed structured illumination and a single-pixel photon counting detector is built. The proposed multiresolution photon counting 3D imaging technique acquires a high-resolution 3D image from a coarse image and details at successfully finer resolution sampled by Hadamard multiplexing along with the wavelet trees. The detected power is significant increased thanks to the Hadamard multiplexing. Both the required measurements and the reconstruction time can be significant reduced, which makes the proposed technique suitable for scenes with high spatial resolution. Since the depth map is retrieved through a linear inverse Hadamard transform instead of the computational intensive optimization problems performed in CS, the time consumed to retrieve the depth map can be also reduced, and thus it will be suitable for applications of real-time compressed 3D imaging such as object tracking. Even though the resolution of the final 3D image can be high, the number of measurements remains small due to the adaptivity of the wavelet-trees-based sampling strategy. The adaptive sampling technique is quality oriented, allowing more control over the image quality. The experimental results indicate that both the intensity image and depth map of a scene at resolutions up to 512×512 pixels can be acquired and retrieved with practical times as low as 17 seconds.

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