Abstract: This paper proposes a matching method for remote sensing images, which combines the superiorities of the speeded up robust features (SURF) algorithm and the random sample consensus (RANSAC) algorithm. Firstly, feature detection and pre-matching of images are done by using SURF algorithm. Secondly, the mismatching is wiped out by using RANSAC algorithm. This method solves the mismatching problem of image matching. Integrated experiments on feature detection and matching as well as the settlement of transformation matrix show that the proposed method is effective.

Key words: integral image, box filter, SURF algorithm, Hession matrix, RANSAC algorithm, remote sensing image 

摘要： 综合利用了SURF（speeded up robust features）算法和RANSAC（random sample consensus）算法各自的优势，提出了一种SURF算法和RANSAC算法相结合的遥感图像匹配方法。首先利用SURF算法提取特征点并进行预匹配，然后用RANSAC算法剔除误匹配点对，解决了SURF算法中存在的误差匹配和错误匹配问题。通过实验验证了所提算法的有效性，并且该算法在实际应用中也取得了良好的效果。

关键词: 积分图像, 盒滤波器, SURF算法, Hession矩阵, RANSAC算法, 遥感图像