海军航空大学学报2018，Vol.33Issue(2)：181-186,200,7.DOI:10.7682/j.issn.1673-1522.2018.02.001
基于改进SURF算法的无人机遥感图像拼接方法
Mosaic Method of UAV Images Based on the Improved SURF
摘要
Abstract
Due to the traditional SIFT algorithm, there are many problems such as slow operation, mis-matching and com-putational complexity in UAV remote sensing image splicing, which can not meet the real-time requirements of remote sensing image processing, and there are exposure differences between the collected images. In this case, the direct super-position and splicing may cause ghosting misalignment at the boundary. In this paper, an improved SURF algorithm and fu-sion algorithm for remote sensing image mosaic of drones were proposed. Firstly, in the feature detection phase, the SURF algorithm and the Harris corner detection algorithm were combined to obtain the feature points and feature descriptors of the image quickly. In the feature matching stage, it was divided into two steps, whinch were rough matching and fine match-ing. The rough matching of the feature points between the stitched images and the fine matching of the mismatched points were eliminated by using the RANSAC algorithm. In the image fusion stage, a weighted average algorithm based on dis-tance was used for image fusion. The final experiment showed that the processing speed of the proposed algorithm was im-proved by nearly 5 times compared with the traditional SUFT algorithm. Compared with other improved algorithms, the matching accuracy was also improved, and this algorithm could effectively improve the quality of the image mosaic. The ef-fect solved the problem that the splicing marks, ghosts, dislocations and other phenomena might occur.关键词
无人机遥感图像/图像拼接/SURF/KNN/RANSACKey words
UAV remote sensing image/image stitching/SURF/KNN/RANSAC分类
信息技术与安全科学引用本文复制引用
么鸿原,王海鹏,焦莉,林雪原..基于改进SURF算法的无人机遥感图像拼接方法[J].海军航空大学学报,2018,33(2):181-186,200,7.基金项目
国家自然科学基金资助项目(61471383) （61471383）
