基于SIFT点特征和Canny边缘特征匹配的多源遥感影像配准研究

针对多源遥感影像的配准，提出了一种结合SIFT点特征和Canny边缘特征匹配的配准算法。该算法首先采用SIF7算法提取点特征并进行影像粗配准，在获得初始仿射变换参数后，采用Canny算法提取边缘特征，并采用成本函数法进行边缘点匹配，经粗差滤除后得到有效的匹配特征点对，随之进行影像精配准。该算法结合了SIFT、算法和Canny算法的优点，解决了多源遥感影像因辐射差异和几何差异造成的难以正确配准的问题。实验结果表明，算法具有较强的鲁棒性，并取得了较好的配准精度。

Multi-sensor Image Registration Algorithm Based on SIFT Points and Canny Edge Features Matching

To resolve multi-sensor remote sensing image registration, an algorithm combining scale invariant feature transform(SIFT) point features and Canny edge feature matching was proposed. First,this algorithm uses SIFT to extract point feature and conduct image coarse registration. Then after getting the initial affine transformation parameters,this algorithm uses Canny algorithm to extract edge feature and then uses the cost function for edge matching. Last, after getting the effective matching feature points by filtering outliers, this algorithm conducts image accurate registration. I}his algorithm combines the advantages of SIFT and Canny, and solves the problem that the multi-sensor remote images are difficult for correct registration because of geometric differences and radiometric differences. Experimental results show that this algorithm has strong robustness, and achieves high registration accuracy.