中文摘要：

提出了一种改进的基于空间结构约束的迭代最近点（ICP）影像配准方法.该方法通过结合特征点的空间结构相似性和特征相似性获得特征点的匹配矩阵,其中特征相似性通过特征点的局部特征描述算子进行计算,空间相似性则通过特征点的空间位置进行计算.特征点之间的空间结构相似性不仅包括了对应特征点之间的空间距离,还包含了特征点到邻近特征点的空间距离.在匹配过程中,分别从参考影像和待配准影像的角度出发,实现了匹配的对称性处理.通过对具有不同影像特征的真实遥感影像进行实验,结果表明该算法具有较高的配准精度.

英文摘要：

A modified iterative closest point （ICP） image registration algorithm based on spatial structure constraint is proposed to overcome the matching ambiguity of remote sensing image registration caused by outliers. This algorithm combines the similarities of spatial structure and feature to determine matching matrix of feature points, among which the similarity of feature is achieved by a local-feature descriptor while the similarity of spatial structure is calculated by spatial coordinates of feature points. Different to current structure-based algorithms, the similarity of spatial structure contains not only spatial distance of corresponding feature points but distance of neighboring ones. And in matching process, the matching pairs are determined by a bidirectional matching criterion from the view of reference and sensed images. Experiments on real remote sensing images of different characteristics show that this algorithm can enhance registration accuracy.