基于特征点的图像配准方法研究

Image Registration Based on Feature

图像配准是将不同条件下(时间、传感设备、气候、角度等)得到的两幅或者多幅图像进行匹配、叠加的过程。通常,每种配准技术都是针对某一类具体应用的,有一定的局限性。文中提出了一种融合的、基于特征点的图像配准方法,首先采用小波变换和USAN区域特性相结合的角点检测方法,然后利用互相关和RANSAC相结合的方法进行特征点匹配,最后采用薄板样条法求解点变换矩阵。通过这种方法可以弥补不同配准方法的不足,提高配准精度。通过对人物、景物等大量图像进行实验分析,证明此算法具有很好的配准精度、环境适应性和实时性。

Image registration is a process of matching and superimposing two or more images obtained under different conditions （time, sensing equipment, climate, angle, etc. ）. Typically, each registration technique is specific to a particular class of application, with some limitations. An fusion image registration algorithm based on feature is presented in this thesis. Firstly, the corner detection method is com- bined with wavelet transform and USAN regional features. Then, the feature points are matched by cross correlation and RANSAC （Random Sample Consensus）. Finally, the thin-plate spline algorithm is adopted. This method can make up for the shortcomings of different regis-tration methods to improve the accuracy. Through experiments on a large number of images, such as characters and scenes, it is proved that the algorithm has good registration accuracy, environmental adaptability and real-time.