基于二元函数拟合的遥感图像配准方法

Registration of Remote Sensing Images Based on Binary Function Fitting

为了提高寻找光学遥感图像配准控制点的精确度，提出了一种基于二元函数拟合的遥感图像配准方法。利用基于模板的互信息法在可能区域上搜索同名点，与经典的利用区域的互信息最大值的坐标作为同名点坐标不同，对搜索过程中生成的测度矩阵进行二维高斯拟合，以高斯函数顶点位置作为配置控制点的同名点坐标值。利用配准控制点实现遥感图像的配准。分别利用该算法和传统互信息法对某地区的光学遥感图像进行配准，实验结果表明，该算法配准精度高于普通方法，配准误差小于0.1，精度达到亚像素级。基本满足光学遥感图像配准要求，为后续进一步融合、变化检测等应用提供必要的数据支持。

A remote sensing image registration method based on binary function fitting is proposed to improve the accuracy of searching for optical remote sensing image registration control points. Mutual information method based on template is used to search homonymy points in possible areas, metric matrix is generated by two-dimensional Gaussian function in the process of searching and the vertex position of the Gaussian function is set as the coordinate values of homonymy points, which is different from using the maximum coordinate values of mutual information as the coordinate values of homonymy points in the classical used region. The remote sensing image registration is completed by registration control points. This proposed algorithm and traditional mutual information method are used for a particular area of optical remote sensing image registration respectively. The experimental results show that this proposed registration precision is higher than the ordinary method, the registration error is less than 0.1 and the precision achieves sub-pixel level. In general, this method can satisfy the requirement of optical remote sensing image registration basically and provide necessary data support for subsequent further fusion, change detection and other applications.