Three-dimensional ghost imaging lidar via sparsity constraint
文献类型：期刊论文
| 作者 | Han, Shensheng; Xu, Wendong; Chen, Mingliang; Yu, Hong; Zhao, Chengqiang; Gong, Wenlin |
| 刊名 | Sci Rep
 |
| 出版日期 | 2016 |
| 卷号 | 6 |
| 通讯作者 | gongwl@siom.ac.cn |
| 英文摘要 | Three-dimensional (3D) remote imaging attracts increasing attentions in capturing a target's characteristics. Although great progress for 3D remote imaging has been made with methods such as scanning imaging lidar and pulsed floodlight-illumination imaging lidar, either the detection range or application mode are limited by present methods. Ghost imaging via sparsity constraint (GISC), enables the reconstruction of a two-dimensional N-pixel image from much fewer than N measurements. By GISC technique and the depth information of targets captured with time-resolved measurements, we report a 3D GISC lidar system and experimentally show that a 3D scene at about 1.0 km range can be stably reconstructed with global measurements even below the Nyquist limit. Compared with existing 3D optical imaging methods, 3D GISC has the capability of both high efficiency in information extraction and high sensitivity in detection. This approach can be generalized in nonvisible wavebands and applied to other 3D imaging areas. |
| 收录类别 | SCI |
| 资助信息 | Hi-Tech Research and Development Program of China [2013AA122901, 2011AA120101]; National Natural Science Foundation of China [61571427]; Youth Innovation Promotion Association CAS [2013162] |
| WOS记录号 | WOS:000375980700001 |
| 源URL | [http://ir.siom.ac.cn/handle/181231/27836]  |
| 专题 | 上海光学精密机械研究所_量子光学重点实验室 |
| 作者单位 | 中国科学院上海光学精密机械研究所 |
| 推荐引用方式 GB/T 7714 | Han, Shensheng,Xu, Wendong,Chen, Mingliang,et al. Three-dimensional ghost imaging lidar via sparsity constraint[J]. Sci Rep,2016,6. |
| APA | Han, Shensheng,Xu, Wendong,Chen, Mingliang,Yu, Hong,Zhao, Chengqiang,&Gong, Wenlin.(2016).Three-dimensional ghost imaging lidar via sparsity constraint.Sci Rep,6. |
| MLA | Han, Shensheng,et al."Three-dimensional ghost imaging lidar via sparsity constraint".Sci Rep 6(2016). |
入库方式： OAI收割
来源：上海光学精密机械研究所
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