结合链码和小面元特征的图像配准算法

Image registration algorithm combined with chain code and patches

传统的基于链码特征的图像配准中,往往存在算法复杂度高,有效边缘难以提取,配准精度不理想等问题。针对这些问题,提出了一种基于小面元和链码特征的遥感图像配准算法。该算法首先提取小面元进行预处理和一次匹配,以更有效地提取封闭边界,同时降低算法复杂度;其次,根据封闭边界链码的相似函数和区域不变矩匹配策略建立边界对应关系,实现区域之间的二次匹配;最后提取匹配区域的质心即匹配点进行一致性检测,并估算仿射变换参数进行图像配准。实验结果显示,该算法快速稳健,具有更高的配准精度。

In the traditional image registration method which is based on the feature of chain code,there are many drawbacks like high computational complexity,hard to extract boundary,not ideal accuracy and so on.This paper presents a new algorithm for image registration which is based on the features of patches and chain code.First,with patch detection,the closed boundary regions in both images are extracted and the computational complexity is reduced.Next,the correspondence of closed boundary regions is developed by chain code correlation and invariant moments.Finally,the center of gravity in the correspondent regions is used as matching points and a consistency check is applied.The affine transformation parameter is estimated by matching points.Experimental results show that the method is fast and robust,and the registration accuracy is better.