Liu Zhiwen, Xu Gen, Xiao Jiangjian, Yang Jingxiang, Wang Ziyang, Cheng Siyuan
Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, China.
Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
J Imaging. 2023 Mar 11;9(3):67. doi: 10.3390/jimaging9030067.
This study aimed to achieve the accurate and real-time geographic positioning of UAV aerial image targets. We verified a method of registering UAV camera images on a map (with the geographic location) through feature matching. The UAV is usually in rapid motion and involves changes in the camera head, and the map is high-resolution and has sparse features. These reasons make it difficult for the current feature-matching algorithm to accurately register the two (camera image and map) in real time, meaning that there will be a large number of mismatches. To solve this problem, we used the SuperGlue algorithm, which has a better performance, to match the features. The layer and block strategy, combined with the prior data of the UAV, was introduced to improve the accuracy and speed of feature matching, and the matching information obtained between frames was introduced to solve the problem of uneven registration. Here, we propose the concept of updating map features with UAV image features to enhance the robustness and applicability of UAV aerial image and map registration. After numerous experiments, it was proved that the proposed method is feasible and can adapt to the changes in the camera head, environment, etc. The UAV aerial image is stably and accurately registered on the map, and the frame rate reaches 12 frames per second, which provides a basis for the geo-positioning of UAV aerial image targets.
本研究旨在实现无人机航空图像目标的精确实时地理定位。我们通过特征匹配验证了一种将无人机相机图像在地图（带有地理位置）上进行配准的方法。无人机通常处于快速运动中，且涉及机头的变化，而地图具有高分辨率且特征稀疏。这些原因使得当前的特征匹配算法难以实时准确地将两者（相机图像和地图）进行配准，即会出现大量错配。为解决此问题，我们使用了性能更优的SuperGlue算法来匹配特征。引入了层和块策略，并结合无人机的先验数据，以提高特征匹配的准确性和速度，还引入了帧间获得的匹配信息来解决配准不均匀的问题。在此，我们提出用无人机图像特征更新地图特征的概念，以增强无人机航空图像与地图配准的鲁棒性和适用性。经过大量实验，证明所提方法可行，且能适应机头、环境等的变化。无人机航空图像在地图上稳定且准确地配准，帧率达到每秒12帧，为无人机航空图像目标的地理定位提供了依据。
