面向可见光和SAR影像配准的特征点检测  

Feature point detection for optical and SAR remote sensing images registration

作　　者：王丽娜 梁怀丹 王中石[2] 徐瑞 石广丰[1] WANG Lina;LIANG Huaidan;WANG Zhongshi;XU Rui;SHI Guangfeng(College of Electro-Mechanical Engineering,Changchun University of Science and Technology,Changchun 130022,China;Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China)

机构地区：[1]长春理工大学机电工程学院,吉林长春130022 [2]中国科学院长春光学精密机械与物理研究所,吉林长春130033

出　　处：《光学精密工程》2022年第14期1738-1748,共11页Optics and Precision Engineering

基　　金：国家自然科学基金项目(No.62103396);吉林省自然科学基金项目(No.YDZJ202101ZYTS048);吉林省教育厅科学研究项目(No.JJKH20210811KJ)。

摘　　要：由于可见光和SAR影像间的非线性辐射差异和SAR斑点噪声的影响,现有算法在对SAR影像进行特征点提取时,难以保证特征点的重复率,导致匹配性能下降。针对上述问题,本文提出了一种基于相位一致性矩特征的分块Har⁃ris特征点提取算法。首先,对输入图像进行分块操作;其次,定义了相位一致性中间矩,并结合最大矩和最小矩对每个图像块构建相位一致性多矩图;最后,在相位一致性多矩图上设计了投票策略,选取了在多矩图上重复出现超过半数的特征点,即稳定且重复率高的特征点作为最终的特征点。本文采用仿真的可见光和SAR图像作为实验数据,选取了三种不同的特征点检测算法与本文算法进行对比,实验结果表明,该算法能够克服SAR斑点噪声的影响和影像间的非线性辐射差异,有效地提高了特征点的重复率。可见光和SAR图像的配准结果表明,匹配点数较其他三种测试算法分别提高了23、26和35对,均方根误差分别降低了12.6%、37.2%和40.8%,有效地提升了配准算法性能。The influence of SAR speckle noise makes it difficult for the existing state-of-the art algorithms to guarantee the repeatability rate of feature points when extracting them from optical and SAR images ow ing to the nonlinear radiation differences between optical and SAR remote sensing images,which consequently reduce the matching performance.To address the above problems,a Harris feature point extraction algorithm based on phase congruency moment feature is proposed.Firstly,blocking strategy was used to divide the input image into several image blocks;secondly,phase congruency intermediate moments were defined;then,phase congruency multi-moment maps were calculated for each image block;and finally,a voting strategy was designed on the phase congruency multi-moment maps.The feature points that appeared more than half of the time on the multi-moment image were selected as the final feature points.In this study,the simulated optical and SAR images were used as experimental data,and three different feature point detection algorithms were selected for comparison with the proposed algorithm.Experimental results showed that the proposed algorithm can overcome the influence of nonlinear radiation differences between optical and SAR remote sensing images and the SAR speckle noise,improving the repeatability rate of feature points effectively.The registration results on the real optical and SAR images showed that,compared with the other three algorithms,the matching points increased by 23,26,and 35 pairs and the root mean square error decreased by 12.6%,37.2%,and 40.8%,respectively.The performance of registration algorithm was improved effectively.

关 键 词：可见光和SAR影像 非线性辐射差异 斑点噪声 相位一致性 特征点提取 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]