一种基于格网索引优化的遥感影像自动配准算法  

An automatic registration algorithm for remote sensing images based on grid index

作　　者：张萌生 杨树文 贾鑫 臧丽日 ZHANG Mengsheng;YANG Shuwen;JIA Xin;ZANG Liri(Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China;National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China;Gansun Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China)

机构地区：[1]兰州交通大学测绘与地理信息学院,兰州730070 [2]地理国情监测技术应用国家地方联合工程研究中心,兰州730070 [3]甘肃省地理国情监测工程实验室,兰州730070

出　　处：《国土资源遥感》2021年第1期123-128,共6页Remote Sensing for Land & Resources

基　　金：国家重点研发计划(地球观测与导航)“星空地遥感立体监测技术”(编号:2017YFB0504201);国家自然科学基金项目“基于高分辨率卫星影像的彩钢板建筑与城市空间结构演变关系研究”(编号:41761082)共同资助。

摘　　要：针对SIFT算法在遥感影像配准过程中捕获配准点对数量较少和误匹配较多等问题,提出了一种基于格网索引的遥感影像自动配准的算法。首先,采用SIFT算法提取特征点和特征向量,并通过欧氏距离进行匹配;其次,建立格网索引剔除部分误匹配点对,从而提高了随机抽样一致算法的精度;最后,使用多项式几何纠正算法实现遥感影像的精确配准。实验结果表明:该算法比传统分块算法在遥感影像中得到的匹配点对精度更高,并且考虑到不同遥感影像配准场景的差异。This paper proposes an algorithm for automatic registration of remote sensing images based on grid index,aiming at tackling the problems of a small number of registration point pairs and a large number of mismatches captured by the SIFT algorithm in the process of remote sensing image registration.First,SIFT algorithm is used to extract feature points and feature vectors,and matching is made by Euclidean distance;secondly,a grid index is established to eliminate part of the mismatched point pairs,thereby improving the accuracy of the random sampling consensus algorithm;finally,geometric polynomials are used to achieve accurate registration of remote sensing images.The experimental results show that the algorithm has higher accuracy of matching point pairs than the traditional block algorithm in remote sensing images,and takes into account the differences in registration scenes of different remote sensing images.

关 键 词：SIFT 格网索引 随机抽样一致 影像配准 

分 类 号：P237[天文地球—摄影测量与遥感]