为提高遥感图像配准精度,提出了一种基于均匀分布质量的配准控制点筛选方法.首先,以尺度不变特征变换获取控制点,采用随机抽样一致性筛除误匹配控制点,然后对配准图像公共区域分块进行基于分布质量的控制点筛选,采用最小二乘估计仿射变换模型参数,最后对输入图像坐标变换后完成配准.对多种遥感图像的实验结果表明,所提出的方法能有效删除误匹配控制点,使控制点均匀分布,减小配准误差.

In order to improve the registration accuracy of remote sensing image,a method for selecting control points is proposed based on uniform distribution quality.In this method,first,control points are extracted via the scale-invariant feature transform,and wrong matched control points are deleted by means of random sample consensus（RANSAC）.Then,the common area of the image pair is divided into several sub-regions and suitable control points are selected according to the distribution quality.Finally,the parameters of the affine transformation model are estimated through the least squares approximation and the registration is conducted via the coordinate transformation of the input image.Experimental results of various kinds of remote sensing images prove that the proposed method effectively removes the wrong matched control points,guarantees the distribution uniformity of control points and reduces the registration error.