基于无人机航拍图像的关键目标点间距测量研究  

Research on Spacing Measurement of Key Target Points Based on UAV Aerial Image

作　　者：黄皓 Huang Hao(Sichuan Institute Of Industrial Technology,Deyang 618500,China)

机构地区：[1]四川工业科技学院

出　　处：《计算机测量与控制》2019年第7期11-14,31,共5页Computer Measurement &Control

摘　　要：为了解决以往测距方法受到噪声影响而导致测量结果精准度低的问题,提出了基于无人机航拍图像的关键目标点间距测量研究;依据无人机航拍图像上下行链路测距原理,设计测量方案实现流程;利用三轴机光电经纬仪获取关键目标点方位角和高低角,采用灰度信息匹配方法匹配图像,标记参考点;根据参考点生成特征描述子,通过局部自相关函数曲率对多维特征描述子进行分类,并对像素点进行检测,以此提取特征点,通过无人机上下行链路获取的图像信息进行间距测量计算;经过图像坐标变换、重采样、图像增强、图像平滑步骤完成误差修正,实现去燥目的;在地空链路有线测试平台上进行数值分析,由结果可知,基于无人机航拍图像测距结果更为精准,有效提高了在复杂地理环境下方法测量精度。In order to solve the problem of low accuracy of measurement results caused by noise in previous ranging methods, the research of key target point spacing measurement based on UAV aerial image is proposed. According to the principle of up-link and down-link ranging of UAV aerial images, the realization process of measurement scheme is designed. The azimuth angle and elevation angle of the key target point are acquired by the three-axis photoelectric theodolite. The gray information matching method is used to match the image and mark the reference point. The feature descriptors are generated according to the reference points, and the multi-dimensional feature descriptors are classified by curvature of local autocorrelation function, and the pixels are detected to extract the feature points, and the distance between them is measured and calculated by the image information acquired by UAV downlink and downlink. After image coordinate transformation, resampling, image enhancement and image smoothing steps, the error correction is completed to achieve the goal of drying. Through numerical analysis on the ground-to-air link cable test platform, the results show that the ranging results based on UAV aerial images are more accurate, which effectively improves the measurement accuracy in complex geographical environment.

关 键 词：无人机航拍 图像 关键目标点 间距测量 特征描述子 

分 类 号：TP872[自动化与计算机技术—检测技术与自动化装置]