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SURF算法和RANSAC算法相结合的遥感图像匹配方法
引用本文:陈艺虾,孙权森,徐焕宇,耿蕾蕾.SURF算法和RANSAC算法相结合的遥感图像匹配方法[J].计算机科学与探索,2012,6(9):822-828.
作者姓名:陈艺虾  孙权森  徐焕宇  耿蕾蕾
作者单位:南京理工大学计算机科学与技术学院,南京,210094
基金项目:国家自然科学基金No.60773172;高等学校博士学科点专项科研基金No.200802880017;南京理工大学自主科研专项计划资助项目No.2011ZDJH26~~
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

Matching Method of Remote Sensing Images Based on SURF Algorithm and RANSAC Algorithm
CHEN Yixia , SUN Quansen , XU Huanyu , GENG Leilei.Matching Method of Remote Sensing Images Based on SURF Algorithm and RANSAC Algorithm[J].Journal of Frontier of Computer Science and Technology,2012,6(9):822-828.
Authors:CHEN Yixia  SUN Quansen  XU Huanyu  GENG Leilei
Affiliation:School of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing 210094, China
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.
Keywords:integral image  box filter  SURF algorithm  Hession matrix  RANSAC algorithm  remote sensing image
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