最优控制点选取的遥感图像亚像素配准算法

分析了已有图像配准算法应用遥感图像配准方面的面临的问题，针对提高不同模态遥感图像配准精度问题，提出了一种人工辅助多模态图像配准算法。该算法首先由人工对待配准图像(测试图像)和参考图像输入控制点，利用高斯差分算子确定测试图像极值点；其次利用投影变换和最小线性平方差算法计算双边平均配准误差；最后，根据配准误差自动对控制点进行亚像素调整，取得亚像素级控制点匹配，实现遥感图像精确配准。实验结果表明，该算法具备更高的配准精度。 

Remote Sensing Images Sub-pixe Registration Algorithm By Selecting Best Control Points

This paper analyses the defect of the existing image registration algorithm which is applied in remote sensing image registration field. Addressing the problem about improving the accuracy of different modes for remote sensing image registration, it proposed an assisted multi modal image registration algorithm. Firstly inputting control points on test image and the reference image and using DOG（Difference of Gaussian）to determine the precise coordinates of key points on test images. Secondly, the test image and reference image can get a rough registration by using projection transform and linear least square algorithm. Finally the algorithm automatically adjusts the control points by sub-pixel step according to the registration error and achieves the sub-pixel registration result . The experimental results show that, the algorithm has higher registration accuracy.