测绘通报 ›› 2018, Vol. 0 ›› Issue (3): 108-112.doi: 10.13474/j.cnki.11-2246.2018.0086

• 行业观察 • 上一篇    下一篇

一种无人机影像空三加密点抽稀算法

王刊生, 郑亮   

  1. 中交第二公路勘察设计研究院有限公司, 湖北 武汉 430056
  • 收稿日期:2017-11-28 出版日期:2018-03-25 发布日期:2018-04-03
  • 作者简介:王刊生(1964-),男,高级工程师,主要从事公路摄影测量与遥感方面工作。E-mail:wks2000www@163.com
  • 基金资助:

    中交第二公路勘察设计研究院科技研发项目(KJFZ-2015-075)

Aerial Triangulation Points Thinning Algorithm for UAV Image

WANG Kansheng, ZHENG Liang   

  1. CCCC Second Highway Consultants Co. Ltd., Wuhan 430056, China
  • Received:2017-11-28 Online:2018-03-25 Published:2018-04-03

摘要:

在无人机空三加密中,特征点匹配多采用基于计算机视觉的匹配算法进行处理,对稀少的空中三角测量控制点进行控制点位的补充。由于无人机影像分辨率高,细节丰富,使得匹配特征点数量庞大,给后续的区域网平差带来困难。本文提供的空三加密点抽稀算法,可大幅降低加密点的数量,优先保留优质点位,并保证被保留点位均匀分布。

关键词: 无人机, 空三加密, 影像匹配, 点抽稀算法

Abstract:

In UAV aerial triangulation,feature point matching is mostly processed by matching algorithm based on computer vision,to supplement the number of ground control points.Because of the high resolution and rich details of the UAV image,the number of matching feature points is huge,which brings difficulties to the subsequent block adjustment.The points thinning algorithm is provided in this paper,which greatly reduces the number of matching feature points,preserves the high quality points first,and ensures the uniform distribution of the reserved points.

Key words: UAV, aerial triangulation, image matching, points thinning algorithm

中图分类号: