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

Li, X. G.; Ren, C.; Zhang, T. X.; Zhu, Z. L.; Zhang, Z. G.

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.

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Li, X. G. / Ren, C. / Zhang, T. X. / et al: UNMANNED AERIAL VEHICLE IMAGE MATCHING BASED ON IMPROVED RANSAC ALGORITHM AND SURF ALGORITHM. 2020. Copernicus Publications.

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