基于扩展相位一致性特征和空间关系约束的异源遥感影像配准方法  

Heterogenous Remote Sensing Image Registration based on Extended Phase Consistency Feature and Spatial Relationship Constraint

作　　者：郑耀 杨树文 武锦沙 付昱凯 寇瑞雄 ZHENG Yao;YANG Shuwen;WU Jinsha;FU Yukai;KOU Ruixiong(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;Gansu Province 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,甘肃兰州730070 [2]地理国情监测技术应用国家地方联合工程研究中心,甘肃兰州730070 [3]甘肃省地理国情监测工程实验室,甘肃兰州730070

出　　处：《遥感技术与应用》2025年第1期144-155,共12页Remote Sensing Technology and Application

基　　金：国家重点研发计划项目(2022YFB3903604);中央引导地方科技发展资金项目(22ZY1QA005);国家自然科学基金项目(42161069);甘肃省在站博士后专项(23JRRA910)共同资助。

摘　　要：针对异源影像配准中存在误匹配率较高和配准精度较低的问题,提出了一种基于扩展相位一致性和空间关系约束的异源影像配准算法(Extended Phase Consistency Spatial Relationship Constraints,EPC―SRC)。首先,设计了一种基于自适应加权力矩图的分块Harris特征检测方法,用于检测稳定、均匀分布且可重复的关键特征点;其次,采用多尺度加权最大索引图(Multiscale Weighted Maximum Index Map,MSW―MIM)结合改进的GLOH描述符结构(Gradient Location Orientation Histogram―like,GLOH―like)构建鲁棒的特征描述符,以提高特征描述符的可区分性;最后,采用马氏距离和边缘化样本共识(Marginalizing Sample Consensus,MAGSAC)方法获取同名点,利用空间关系约束实现特征点精确匹配,并进行迭代求解优化单应性矩阵实现高精度影像配准。通过10组异源遥感影像配准实验对比及分析,结果表明:该方法综合性能明显优于其他对比算法,并且在配准精度方面取得了最好的效果。This paper introduces a heterogeneous image registration algorithm called Extended Phase Consisten⁃cy Spatial Relationship Constraints(EPC-SRC).The objective is to address challenges related to a high mis⁃matching rate and low registration accuracy encountered in registering heterogeneous images.Initially,we pres⁃ent a chunked Harris feature detection method based on an adaptive weighted moment map.This method aims to identify stable,uniformly distributed,and repeatable key feature points.Subsequently,a multiscale weighted maximum index map(MSW-MIM),combined with an enhanced GLOH histogram-like(GLOH-like)ap⁃proach,is employed to construct descriptors.This strategy enhances the distinguishability of descriptors,con⁃tributing to improved accuracy.Finally,the Marginalizing Sample Consensus(MAGSAC)method is utilized to establish corresponding points.This facilitates precise feature point matching by incorporating spatial relation⁃ship constraints.An iterative approach is employed to solve the homography matrix,resulting in high-precision image registration.A comparative analysis involving ten experiments on aligning heterogeneous remote sensing images demonstrates that our proposed method significantly outperforms other algorithms.Notably,our ap⁃proach attains superior results in terms of matching accuracy.

关 键 词：异源遥感影像 影像配准 相位一致性 空间关系约束 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]