首页> 外文会议>International Geoscience and Remote Sensing Symposium >Accuracy analysis of UAV remote sensing imagery mosaicking based on structure-from-motion
【24h】

Accuracy analysis of UAV remote sensing imagery mosaicking based on structure-from-motion

机译:基于动结构的无人机遥感影像镶嵌精度分析

获取原文

摘要

Structure-From-Motion (SFM) method is based on the same scene and different angles of the captured sequence of image, then calculate the feature points in the photogrammetric coordinate system of three-dimensional coordinates and camera parameters. SFM can directly generated orthophoto map just by captured overlapping images, but mosaicking accuracy has not to be verified. The purpose of this study is that verify the feasibility and accuracy of SFM method in UAV image mosaic. The process of UAV imagery mosaicking based on SFM method was elaborated, and the test image was mosaicked with UAV imagery processing software which based on SFM. The result: (1) UAV imagery mosaicking based on SFM algorithm has low accuracy on geographic positioning because of the low precision POS. But the distancearea measurement with high accuracy, the perimeter accuracy is above 96.6% and the area accuracy is above 93.2%. (2) The image had high accuracy after geometric correction using ground points. When 5 ground points were used, the mean value of absolute error was 0.60 m. The study showed: (1) the accuracy of perimeter and area can basically meet the accuracy requirements of distancearea measurement in agricultural applications. (2) the orthophoto map was rectified by ground control point can significantly improve the geo-location precision of the image.
机译:基于运动的结构(SFM)方法是基于相同场景和不同角度捕获的图像序列,然后在三维坐标系和相机参数的摄影测量坐标系中计算特征点。 SFM可以仅通过捕获重叠图像直接生成正射影像图,但是镶嵌精度无需验证。这项研究的目的是验证SFM方法在无人机图像拼接中的可行性和准确性。阐述了基于SFM方法的无人机图像镶嵌的过程,并利用基于SFM的无人机图像处理软件对测试图像进​​行了镶嵌。结果:(1)由于POS精度低,基于SFM算法的无人机图像镶嵌在地理定位上精度较低。但距离面积测量具有较高的精度,周界精度在96.6%以上,面积精度在93.2%以上。 (2)使用地面点进行几何校正后,图像具有较高的精度。当使用5个接地点时,绝对误差的平均值为0.60 m。研究表明:(1)周长和面积的精度基本可以满足农业应用中测距面积的精度要求。 (2)通过地面控制点对正射影像进行校正,可以显着提高图像的地理位置精度。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号