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首页> 外文期刊>Advances in Science, Technology and Engineering Systems >A Method for Mosaicking Aerial Images based on Flight Trajectory and the Calculation of Symmetric Transfer Error per Inlier
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A Method for Mosaicking Aerial Images based on Flight Trajectory and the Calculation of Symmetric Transfer Error per Inlier

机译:基于飞行轨迹的摩沙度图像和计算每inlier对称转移误差的计算方法

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In recent years, development of aerial autonomous systems and cameras have allowed increasing enormously the number of aerial images, and their applications in many research areas. One of the most common applications is the mosaicking of images to improve the analysis by getting representations of larger areas with high spatial resolution. This paper describes a simple method for mosaicking aerial images acquired by unmanned aerial vehicles during programmed flights. The images were acquired in two scenarios: a city and a forest in the Peruvian Amazon, for vegetation monitoring purposes. The proposed method is a modification of the automatic homography estimation method using the RANSAC algorithm. It is based on flight trajectory and the calculation of symmetric transfer error per inliers. This method was implemented in scientific language and the performance was compared with a commercial software with respect to two aspects: processing time and geolocation errors. We obtained similar results in both aspects with a simple method using images for natural resources monitoring. In the best case, the proposed method is 6 minutes 48 seconds faster than the compared software and, the root mean squared error of geolocation in X-axis and Y-axis obtained by proposed method are less than the obtained by the compared software in 0.5268 and 0.5598 meters respectively.
机译:近年来,空中自治系统和相机的发展允许在许多研究领域的空中图像的数量和应用中的应用增加。其中一个最常见的应用程序是通过在具有高空间分辨率的较大区域的表示来改善分析来改善分析。本文介绍了一种简单的方法,用于在编程飞行期间由无人驾驶飞行器获取的空中图像的简单方法。图像是在两种情况下获取的:植被监测目的的秘鲁亚马逊的城市和森林。所提出的方法是使用RANSAC算法的自动相同估计方法的修改。它基于飞行轨迹和每个inliers对称转移误差的计算。该方法以科学语言实施,并将性能与商业软件相对于两个方面进行比较:处理时间和地理位置错误。我们在两个方面获得了类似的结果,这两个方面都使用图像用于自然资源监控的简单方法。在最佳情况下,所提出的方法比比较的软件快6分48秒,并且通过所提出的方法获得的X轴和Y轴的地理位置的根平均平方误差小于由比较软件在0.5268中获得的和0.5598米。

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