一种基于非线性扩散方程和Hausdorff测度理论的SAR图像与光学图像配准方法

Matching Optical Image to SAR Image Using Nonlinear Equation and Hausdorff Distance

该文提出了一种新的利用非线性扩散方程与Hausdorff测度的合成孔径雷达(SAR)图像与可见光图像的配准算法。在此算法中,首先利用非线性扩散方程的SAR图像分割算法获得SAR图像与光学二值图像中相对应的闭合区域特征,将闭合区域质心坐标重合后,被提取特征可通过Hausdorff测度与遗传算法对图像进行快速粗匹配。在粗配准的基础上最后使用二值图像的相关度来进行精配准。实验结果表明,本文方法鲁棒性好,配准精度高,能自动完成存在较大坐标平移、角度变换、尺度缩放的待配图像的配准。

This paper describes a new method for matching SAR image and optical image. First, regularizing anisotropic heat diffusion equations is used for segmenting closed-boundary regions in SAR image. After superposing the center of mass of closed-boundary regions, Haudorff distance and genetic algorithm are used to determine scaling and rotation parameters respectively. Finally, the affine-transformed result is refined by binary image correlation to achieve high precise registration. Experimental results indicated that this method can perform automatic registration under precision acquirement for images which differ by translation, rotation and scaling.