提出了一种基于几何结构属性的光学和合成孔径雷达(Synthetic Aperture Radar, SAR)影像配准方法.该方法引入了具有光照不变性的相位一致性模型进行影像特征提取, 采用该模型的强度和方向信息构建了一种几何结构特征描述符—相位一致性方向直方图(histogram of orientated phase congruency, HOPC), 并根据该描述符间的欧式距离定义了影像匹配的相似性测度(称为HOPCn).该测度能表示影像间的几何结构相似性.通过选择4组光学和SAR影像进行试验, 结果表明, HOPCn能有效率的抵抗影像间的非线性辐射差异, 并且其匹配性能好于经典的相似性测度.另外, 也设计了一种基于HOPCn自动的配准方法, 试验结果证明了该方法的有效率和鲁棒性.

This paper proposes an automatic registration method for optical and Synthetic Aperture Radar (SAR) images based on geometric structural properties. In the proposed method, the phase congruency feature with photometric invariance is first introduced for image feature extraction, and then both the magnitude and orientation information of phase congruency are used to build a geometric structural feature descriptor named HOPC (Histogram of Orientated Phase Congruency). A similarity metric named HOPCn is defined for image matching by using the Euclidean distance of the descriptors. This similarity metric can capture the geometric structural similarity between images, and has been tested using 4 pairs of optical and SAR images. Experimental results show that HOPCn is robust to non-linear radiometric differences, and outperforms the state-of-the-art similarity metrics such as correlation coefficient and mutual information. Moreover, this paper also design an automatic registration method based on HOPCn. Experimental results demonstrate the effectiveness and robustness of the proposed method.