基于特征的SAR图像与光学图像自动配准

Feature-based automatic registration for SAR and optical remote sensing images

针对现有配准方法在用于SAR图像和光学图像配准时,存在受SAR图像相干斑噪声影响大,手工选取配准点精度低等缺点,提出了一种基于区域特征提取的图像配准方法.对SAR图像首先进行相干斑噪声抑制,并采用图像分割的方法提取出封闭区域的边界作为特征,然后与可见光中提取的边缘利用闭合区域边缘链码的相关寻求匹配,精确配准的误差达到子象素级水平.实验结果表明,该方法能够以较高的精确度从SAR图像中提取配准控制点,从而实现了多传感器图像的自动配准.

In the registration for SAR and optical images, traditional methods are limited by SAR speckle noise and the accuracies of selected registration control points (RCP). A new registration method based on region features is presented. The speckle noises in SAR image are suppressed first and then image segmentation is used to extract close regions as invariable features. Meanwhile, the close contours in optical image are extracted by edge extraction. Next, the precise feature matching is made by chain-code correlation and registration accuracy of sub-pixel is obtained. Experimental results show that the method can extract RCPs with high accuracy and accomplish the automatic registration for multi-sensor images.