可见光图像与合成孔径雷达图像的快速配准  

Fast Registration of Visible light and Synthetic Aperture Radar Images

作　　者：谢志华 刘晶红[1] 孙辉[1,2] 彭佳琦 Xie Zhihua;Liu Jinghong;Sun Hui;Peng Jiaqi(Department of Airborne Optical Imaging and Measurement,Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun,Jilin 130033,China;University of Chinese Academy of Sciences,Beijing 100049,China;First Military Representative Office in Changchun,Changchun,Jilin 130033,China)

机构地区：[1]中国科学院长春光学精密机械与物理研究所航空光学成像与测量重点实验室,吉林长春130033 [2]中国科学院大学,北京100049 [3]驻长春地区第一军事代表室,吉林长春130033

出　　处：《激光与光电子学进展》2020年第6期329-337,共9页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(60902067);吉林省科技发展计划资助项目(20180201054SF)。

摘　　要：针对异源图像配准算法复杂度高且处理速度慢的问题,提出了一种可见光图像与合成孔径雷达(SAR)图像的快速配准算法。在图像预处理阶段去除可见光图像和SAR图像中的冗余信息,分别采用高斯低通滤波和非局部均值滤波(NLM)算法对两种不同类型的图像进行滤波。然后采用多尺度Harris方法检测并提取特征点,利用梯度位置方向直方图(GLOH)对特征点进行描述子构造。最后,基于反馈机制重构原始图像中的特征点,得出待匹配的特征点在原始图像中的实际位置,从而完成原始图像中的特征点重构及匹配。实验结果表明:相比SIFT-M(Scale invariant feature transform-modification)算法,该算法在平均配准精度维持在80%以上的前提下显著缩短了运行时间,具有重要的应用价值。Aiming at the problem of high complexity and low processing speed of heterologous image registration algorithms,a fast registration algorithm of visible light and synthetic aperture radar(SAR)images is proposed.In the image preprocessing stage,the redundant information in visible light and SAR images is removed,and two different types of images are filtered respectively with Gauss low-pass filter and non-local mean filter(NLM)algorithms.Then,the multi-scale Harris method is used to detect and extract feature points,and the gradient position orientation histogram(GLOH)method is used to construct descriptors of feature points.Finally,the feature points in the original image are reconstructed based on the feedback mechanism,and the actual position of the feature points to be matched in the original image is got,so as to complete the reconstruction and matching of the feature points in the original image.The experimental results show that compared with scale invariant feature transform-modification(SIFT-M)method,this algorithm significantly reduces the running time while maintaining the average registration accuracy of more than 80%,and has important application value.

关 键 词：遥感图像 图像配准 可见光图像 SAR图像 冗余信息 特征点重构 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]