Author Affiliations
Abstract
1 Optoelectronics System Laboratory, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
2 University of Chinese Academy of Sciences, Beijing 100049, China
3 School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
4 College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing 100049, China
This Letter proposes a coordinate difference homogenization matching method to solve motion influence in three-dimensional (3D) range-intensity correlation laser imaging. Firstly, features and feature pairs of gate images are obtained by speeded-up robust figures and bi-directional feature matching methods. The original mean value of the feature-pair coordinate differences is calculated. Comparing the coordinate differences with the original mean value, the wrong feature pairs are removed, and then an optimized mean value is updated. The final feature-pair coordinates are re-registered based on the updated mean value. Thus, an accurate transformation is established to rectify motion gate images for 3D reconstruction. In the experiment, a 3D image of a tower at 780 m is successfully captured by our laser gated imaging system on a pan–tilt device.
280.0280 Remote sensing and sensors Chinese Optics Letters
2017, 15(10): 102802
1 中国科学院大学, 北京 100049
2 中国科学院半导体研究所光电系统实验室, 北京 100083
针对目前视频监控领域里目标发现、识别和辨认没有统一的国际标准和行业标准问题, 对比分析了传统视频监控目标检测标准和红外热成像约翰逊准则, 提出了基于约翰逊准则的视频监控目标检测性能评估方法, 以等效条纹线对数代替传统模拟视频监控DRI标准中的目标-屏幕比, 建立了CCTV Johnson-DRI标准。通过线对数绝对量化的评价标准更利于数字视频监控应用中目标发现、识别和辨认的性能评估。最后将提出的CCTV Johnson-DRI标准应用到激光夜视系统, 进行了目标发现、识别和辨认实验, 实验结果表明: 所提出方法的有效性以及与传统视频监控DRI标准的等效性。该方法可用于白天彩色视频监控, LED/激光夜视等安防视频监控领域目标发现、识别和辨认相关性能的评估及系统指标设计。
视频监控 约翰逊准则 视频监控目标检测标准 目标发现 目标识别 目标辨认 video surveillance Johnson criteria video-surveillance DRI standardization target detection target recognition target identification 红外与激光工程
2016, 45(12): 1217003
