基于特征点的多光谱遥感图像配准

Multi-spectral Remote Sensing Image Registration Based on Feature Point

提出一种基于特征点的多光谱遥感图像配准算法。首先在图像上建立二级规则网格,根据信息熵值及特征分布均匀性准则选取特征网格;然后利用Forstner算子在特征网格中提取特征点,针对多光谱图像的特点,利用基于相关性原理的粗匹配和改进的基于空间距离约束的精匹配确立特征点的对应关系;最后通过仿射变换得到配准后的图像,并用均方根误差评价配准效果。实验结果表明,该方法计算速度快,且能够达到亚像素级配准精度。

A registration method for multi-spectral remote sensing image based on feature points was proposed.First,a two-degree regular mesh was formed on the image,and feature grids were chosen according to entropy and uniformity principle.Then feature points were detected by Forstner operate in feature grids.Due to the characteristic of multi-spectral images,the course matching step was achieved by Cross-Correlation theory,and improved space distance constraint was used in fine matching step.Finally,registered image was obtained by affine transformation.RMSE was applied to evaluate the method.The experimental results clearly indicate that the approach we proposed is efficient with sub-pixel precision.