一种基于封闭均匀区域的SAR图像配准方法

为克服图像间灰度差异、旋转差异和尺度差异对SAR图像配准精度的影响，该文利用均匀区域在SAR图像中的灰度统计特性，提出一种基于稳定封闭均匀区域的SAR图像配准算法。首先基于多尺度非线性扩散理论，提取得到轮廓保持性较好的封闭均匀区域；然后构建具有仿射不变性的区域特征，采取基于多边形拟合的区域粗匹配方法和基于重合度的区域精匹配方法，实现由粗至精的区域匹配；最后用匹配区域的质心点构建图像变换模型。实验结果表明，该算法配准精度高，能有效克服待配准图像之间的灰度差异、旋转差异和尺度差异，对噪声具有较好的适应性。

SAR Image Registration Algorithm Based on Closed Uniform Regions

In order to overcome the influence of gray difference, rotation difference and scale difference on image registration accuracy, the gray statistic property of uniform regions in SAR images is utilized and a SAR image registration algorithm based on stable closed uniform regions is proposed. Firstly, based on the multi-scale nonlinear diffusion theory, closed uniform regions with good contour pervserving ability are respectively extracted from two images. Secondly, two affine-invariant region features based on polygon fitting and coincidence degree are constructed to realized the coarse-to-fine region matching. Finally, the centroids of matched regions are used to construct the transform model between two images. Experimental results demonstrate that, the proposed algorithm has high registration accuracy, and is effective for gray difference, rotation difference and scale difference, moreover, it has high adaptability to noise.