一种图像快速配准算法的研究

Study of Image Registration Fast Algorithm

在基于小波分解和互信息测度的图像配准方法的基础上,提出一种改进的快速图像配准算法。首先,对图像进行小波分解,以分解后的图像的近似分量进行配准,利用互信息最大化作为相似性测度,并结合粒子群优化算法和鲍威尔算法为优化策略搜索最优配准参数。实验结果显示,此方法在得到较高的配准精度和鲁棒性的情况下,还大大减少了运算量,提高了配准的速度。

By expatiating image registration method based on wavelet transformation and mutual information, an improved image registration algorithm was proposed. The low - frequency images of wavelet decomposition are used to register; the mutual information was used to be a scale of similarity to two registered images. A new optimization algorithm, which is a hybrid of particle swarm optimization and Powell algorithm, is used in this paper. The experiment shows that this algorithm reduces the amount of computation largely and improves the speed of image registration when the registration precisions have not notable change.