# Improving the Imaging Quality of Ghost Imaging Lidar via Sparsity Constraint by Time-Resolved Technique

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## Abstract

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## 1. Introduction

## 2. Experimental Setup and Image Reconstruction

## 3. Simulation and Experimental Results

## 4. Discussion

## 5. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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**Figure 1.**Schematic of 2D and 3D GISC lidar (ghost imaging lidar via sparsity constraint) with a pseudo-thermal light source. (

**a**) The signal recorded by the bucket detector for a 2D GISC lidar system; (

**b**) The signal recorded by the time-resolved bucket detector for a 3D GISC lidar system. BS: beam splitter; CCD: charge-coupled device camera.

**Figure 2.**Simulation results of imaging a series of resolution plates located about 1230 m away, using 2000 measurements. (

**a**) The original distribution of the resolution plate; (

**b**) The averaged time-resolved signals reflected from the resolution plate; (

**c**) The 2D GISC reconstruction result and (

**d**) the plate’s projection image restored by 3D GISC method. The different colors of the image shown in (

**d**) express different detection distances between the objective lens and the target. MSE: mean squared error.

**Figure 3.**Experimental demonstration results of imaging a building (256 × 256 pixels) at about 1200 m range, using 10,000 measurements (61% of the Nyquist limit). (

**a**) Picture of the invented GISC lidar system; (

**b**) Averaged time-resolved signals reflected from the building; (

**c**) The original target imaged by a telescope with the receiving aperture 140 mm and the focal length 477 mm; (

**d**) 2D GISC reconstruction; (

**e**) The building’s projection image restored by 3D GISC method. The different colors of the image shown in (

**e**) express different detection distances between the objective lens and the target. MSE: mean squared error.

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## Share and Cite

**MDPI and ACS Style**

Gong, W.; Yu, H.; Zhao, C.; Bo, Z.; Chen, M.; Xu, W.
Improving the Imaging Quality of Ghost Imaging Lidar via Sparsity Constraint by Time-Resolved Technique. *Remote Sens.* **2016**, *8*, 991.
https://doi.org/10.3390/rs8120991

**AMA Style**

Gong W, Yu H, Zhao C, Bo Z, Chen M, Xu W.
Improving the Imaging Quality of Ghost Imaging Lidar via Sparsity Constraint by Time-Resolved Technique. *Remote Sensing*. 2016; 8(12):991.
https://doi.org/10.3390/rs8120991

**Chicago/Turabian Style**

Gong, Wenlin, Hong Yu, Chengqiang Zhao, Zunwang Bo, Mingliang Chen, and Wendong Xu.
2016. "Improving the Imaging Quality of Ghost Imaging Lidar via Sparsity Constraint by Time-Resolved Technique" *Remote Sensing* 8, no. 12: 991.
https://doi.org/10.3390/rs8120991