一种基于格网索引优化的遥感影像自动配准算法

An automatic registration algorithm for remote sensing images based on grid index

针对SIFT算法在遥感影像配准过程中捕获配准点对数量较少和误匹配较多等问题,提出了一种基于格网索引的遥感影像自动配准的算法。首先,采用SIFT算法提取特征点和特征向量,并通过欧氏距离进行匹配;其次,建立格网索引剔除部分误匹配点对,从而提高了随机抽样一致算法的精度;最后,使用多项式几何纠正算法实现遥感影像的精确配准。实验结果表明:该算法比传统分块算法在遥感影像中得到的匹配点对精度更高,并且考虑到不同遥感影像配准场景的差异。

This paper proposes an algorithm for automatic registration of remote sensing images based on grid index,aiming at tackling the problems of a small number of registration point pairs and a large number of mismatches captured by the SIFT algorithm in the process of remote sensing image registration.First,SIFT algorithm is used to extract feature points and feature vectors,and matching is made by Euclidean distance;secondly,a grid index is established to eliminate part of the mismatched point pairs,thereby improving the accuracy of the random sampling consensus algorithm;finally,geometric polynomials are used to achieve accurate registration of remote sensing images.The experimental results show that the algorithm has higher accuracy of matching point pairs than the traditional block algorithm in remote sensing images,and takes into account the differences in registration scenes of different remote sensing images.