A Stepwise Refinement Method for Image Matching and Aerotriangulation Using Correction of Local Relative Geometric Distortion

ZHAN Zongqian; LI Yihui; WANG Chendong; ZHENG Li

doi:10.13203/j.whugis20170342

Volume 43 Issue 11

Nov. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(11): 1620-1627. > DOI: 10.13203/j.whugis20170342

ZHAN Zongqian, LI Yihui, WANG Chendong, ZHENG Li. A Stepwise Refinement Method for Image Matching and Aerotriangulation Using Correction of Local Relative Geometric Distortion[J]. Geomatics and Information Science of Wuhan University, 2018, 43(11): 1620-1627. DOI: 10.13203/j.whugis20170342

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A Stepwise Refinement Method for Image Matching and Aerotriangulation Using Correction of Local Relative Geometric Distortion

1.
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China

Funds:

The National Key Research and Development Program of China 2016YFB0501403

the National Natural Science Foundation of China 61871295

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Author Bio:
ZHAN Zongqian, PhD, associate professor, specializes in digital photogrammetry and computer vision. E-mail: zqzhan@sgg.whu.edu.cn
Corresponding author:
ZHENG Li, PhD, associate professor. E-mail: lzheng@sgg.whu.edu.cn
Received Date: October 24, 2017
Published Date: November 04, 2018

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Abstract

Abstract

Aiming at the difficulties of image matching and aerotriangulation for unmanned aerial vehical image in the area with high altitude drop, this paper presents a stepwise refinement method for image matching and aerotriangulation using correction of local relative geometric distortion (CLRGD) which is based on the initial aerotriangulation and rough terrain model. It takes into account the image relative distortion caused by relative tilt of stereo image pairs and topographic relief in which an algorithm for single point accurate matching considering CLRGD has been adopted in the process of normal aerotriangulation. Then image matching and orientation can complement each other so as to improve the accuracy and reliability of matching and aerotriangulation. Experimental analysis proves that the algorithm can do well in the image relative geometric distortion, strengthen the regional network and further improve the accuracy of the aerotriangulation in the area with high altitude drop. In terms of efficiency, the image range of CLRGD is relatively limited due to the use of rough terrain model, so the algorithm can basically meets the actual production needs. If considering that the accurate single point matching used by each tie point has good independence, a parallel algorithm can further improve the efficiency.

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A Stepwise Refinement Method for Image Matching and Aerotriangulation Using Correction of Local Relative Geometric Distortion

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