1. Joint Remote Sensing Research Centre for Rail Transit Project, Southwest Jiaotong University, Chengdu 610031, China;
2. Faculty of Earth and Engineering, Southwest Jiaotong University, Chengdu 610031, China
With the development of the unmanned aerial vehicle(UAV)technique, currently UAV data have been gradually used in application and research fields. Differing from the current UAV matching method that integrates Photogrammetry and Image control points, the novel method presented in this paper is based on the color scale-invariant feature transform (CSIFT) feature to collect the key match points in the reference image and the image to be matched, followed by using the random sample consensus algorithm (RANSAC)method to extract the match points for the final matching result. The authors use an example to verify the feasibility and the validity of the method. Compared with the SIFT method, the accuracy could be increased from 70% to 88%, and the algorithm proposed in this paper can not only guarantee the matching result but also produce less matching points and use less working time.
耿娟, 何成龙, 刘宪鑫. 基于CSIFT特性的无人机影像匹配[J]. 国土资源遥感, 2016, 28(1): 93-100.
GENG Juan, HE Chenglong, LIU Xianxin. UAV image matching based on CSIFT feature. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(1): 93-100.
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2016, Vol. 28 
