International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 67–70, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-67-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 67–70, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-67-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  07 Feb 2020

07 Feb 2020

UNMANNED AERIAL VEHICLE IMAGE MATCHING BASED ON IMPROVED RANSAC ALGORITHM AND SURF ALGORITHM

X. G. Li1, C. Ren1,2, T. X. Zhang3, Z. L. Zhu1, and Z. G. Zhang1 X. G. Li et al.
  • 1College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, China
  • 2Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin, China
  • 3Nanning Exploration & Survey Institute, Nanning, China

Keywords: image registration, SURF, RANSAC, Hessian matrix

Abstract. A UAV image matching method based on RANSAC (Random Sample Consensus) algorithm and SURF (speeded up robust features) algorithm is proposed. The SURF algorithm is integrated with fast operation and good rotation invariance, scale invariance and illumination. The brightness is invariant and the robustness is good. The RANSAC algorithm can effectively eliminate the characteristics of mismatched point pairs. The pre-verification experiment and basic verification experiment are added to the RANSAC algorithm, which improves the rejection and running speed of the algorithm. The experimental results show that compared with the SURF algorithm, SIFT (Scale Invariant Feature Transform) algorithm and ORB (Oriented FAST and Rotated BRIEF) algorithm, the proposed algorithm is superior to other algorithms in terms of matching accuracy and matching speed, and the robustness is higher.