多源遥感影像配准中的SIFT特征匹配改进

针对尺度不变特征变换算法应用于多源遥感影像配准时面临的低效率和误匹配问题，从特征点提取和特征点匹配两个方面对其进行改进。在特征点提取阶段，通过控制特征点数量和分布情况获取均匀分布的特征点；在特征点匹配阶段，采用特征点仿射变换粗匹配、精匹配和误匹配点剔除策略，由粗到精地获取准确的同名点。对多源遥感影像进行配准实验，结果表明，此方法在匹配效率及匹配性能上均优于原始SIFT算法，且配准精度更高。

An Improved SIFT Algorithm for Multi-source Remote Sensing Image Registration

Considering the low efficency and mismatching in SIFT|based multi|source remote sensing image registration, we improve the SIFT algorithm through two aspects of point feature extraction and point feature matching. Firstly, we acquire an appropriate number of well-distributed point features by controlling their number and distribution. Secondly, an optimized strategy is adopted to realize a coarse|to|fine feature point matching approach by applying the initial affine matching, precise matching and mismatching elimination processes. Experiments on several multi|source data sets show that the proposed algorithm performs better than the SIFT algorithm on both efficiency and accuracy.