中文摘要：

低空无人机影像在交通规划、城市管理、应急监控等领域正逐渐体现出其独到的优势,而将影像快速、准确地纠正与配准则是其发挥功用的必要前提。以拍摄于道路交叉口上方的无人机悬停视频为研究对象,探讨对其实现影像抖动纠正配准的方法。视频中的连续影像包含大量的近似地物及移动地物,难以直接采用传统的空间域或频率域方法进行配准。由此,提出了一种基于横道线识别的影像配准方法,经由图斑提取、筛选分类、轴线拟合及影像配准等步骤,实现了影像任意帧间的配准。利用无人机悬停拍摄的交叉口视频进行了验证,结果表明,该方法稳健、有效。

英文摘要：

Low-altitude unmanned aerial vehicle （UAV） images shave increasingly demonstrated unique advantages in the fields of transport planning, urban management, emergency monitoring. To understand the advantages of UAV images, rapid and accurate correction and registration of the image are a necessary premise. This paper takes a image of intersection taken by hovering UAV as its research target, and discusses the method of geometric correction and registration for such images. The image contains a large number of similar features and moving objects, which makes it difficult to be corrected in traditional way, based on spatial domain or frequency domain. Thus, this paper proposes an image registering method based on semantic information extracted from zebra lines. To realize images registration between arbitrary frames, the following steps are necessary： patterns extraction, zebra line patterns preparation and classification, axis fitting and image registration. Finally, a test is performed with a video taken by UAV. The results demonstrate that the method is robust and effective.