测绘科学技术学报2012，Vol.29Issue(2)：153-156,4.DOI:10.3969/j.issn.1673-6338.2012.02.018
改进SIFT算法的小型无人机航拍图像自动配准
Unmanned Aerial Vehicle Serial Aerial Image Automatic Registration Based on Improved SIFT Algorithm
摘要
Abstract
Due to the disperse and regular of view points and the view angle of UAV Aerial Image, the image data was preconditioned at first, then the Harris feature points with SIFT feature vectors were combined, Harris feature points were extracted, the characteristics radius of feature points and SIFT feature vector was calculated, and PCA (Principal Component Analysis) was used to reduce the dimension of SIFT feature vectors. And then the most close method (NN) was used to feature matching, the BBF algorithm was applied to search the nearest neighbor feature for improving the matching speed. Finally, the PROSAC algorithm was used to purify initial feature point matching pairs, and motion model parameters were calculated, the image automatic registration was achieved. The results of experiment proved that such algorithm was more efficient and exact than the classic SIFT algorithm.关键词
无人机航拍图像/图像配准/特征点提取/特征匹配/尺度不变特征变换Key words
UAV aerial image/ image registration/ feature points extraction/ feature match/ scale-invariant feature transform分类
天文与地球科学引用本文复制引用
熊自明,万刚,闫鹤,李明..改进SIFT算法的小型无人机航拍图像自动配准[J].测绘科学技术学报,2012,29(2):153-156,4.基金项目
国家自然科学基金项目(40971239). （40971239）
