摘要
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。
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 the 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.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2008年第10期86-91,共6页
Opto-Electronic Engineering
