摘要
为了实现高精度的图像配准,提出了一种基于相位相关和重采样的亚像素图像配准算法.首先基于相位相关实现像素级的粗定位,然后在粗定位点邻域范围内利用矩阵乘法的离散傅里叶变换(DFT)高倍数重采样,并基于相位相关作重采样区域的像素级定位,实现亚像素级的细定位.文中从理论上证明了基于矩阵乘法的DFT实现部分区域重采样的方法与基于零填充重采样的方法在计算精度上具有等效性.实验结果表明,文中算法的配准精度、计算效率和抗噪性优于基于交互相关和扩展相位相关的亚像素配准算法.
Proposed in this paper is a sub-pixel algorithm based on phase correlation and image resampling for high-accuracy image registration.In this algorithm,first,a pixel-level coarse location is realized using the conventional phase correlation method.Then,a fine step is performed,using the matrix multiplication discrete Fourier transform（DFT） to calculate the resampling region around the coarse point and to further locate the resampling region at a pixel level based on the phase correlation.Moreover,the accuracy equivalence between the matrix multiplication DFT and the zero-padding resampling is proved in detail.Experimental results show that the proposed algorithm is superior to the conventional cross-correlation-based and phase-correlation-based sub-pixel registration algorithms in terms of accuracy,efficiency and noise resistance.
出处
《华南理工大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2010年第10期68-73,78,共7页
Journal of South China University of Technology(Natural Science Edition)
基金
国家自然科学基金重点资助项目(60835001)
关键词
相位相关
重采样
亚像素
配准
矩阵乘法
phase correlation
resampling
sub-pixel
registration
matrix multiplication
