基于投票策略的图像配准算法

摘要

we develop a novel coarse-to-fine method for the registration of the reference and target images,involving the 2D rigid transformation.The proposed method consists of four main steps:utilizing multi-scale Harris comer detector to extract the feature points in the reference and target images;corresponding these points by a novel feature points matching algorithm based on voting strategy,which efficiently eliminates the false and unstable matches;estimating transformation parameters with me matched feature points;refining the transformation parameters with the window-based method.Experimental results demonstrate that the proposed method is able to achieve high accuracy and robustness against noise with low computational burden.%针对二维刚体图像配准,本文提出了一种由粗到细的图像配准方法.该方法首先由多尺度Harris角点检测算法提取出参考图像和目标图像的特征角点,采用基于投票策略的特征点匹配算法进行初步配准,有效地减少假点和不稳定点,然后对变换矩阵参数进行初估计,采用基于窗的精细算法对变换矩阵参数进行精估计,并得到最终的变换矩阵.实验结果表明,该算法具有高精度,对噪声鲁棒和低计算量的特点.