基于Harris角点量与相位相关的亚像素级图像配准方法

摘要

Phase correlation is used to perform image-to-image registration, and the fast direct Fourier-based algorithm ( FDFA) makes registration accuracy up to subpixel, where Fourier components in the Fourier domain and windows in the pixel domain are carefully chosen to eliminate image-boundary effects, making the shift estimation more accurate. This paper proposed a new phase correlation method in which, instead of original images, used the Harris strength of them to determine the image shift. It first extracted feature points from the image using Harris detector, and selected the geometric point. Then placed a circular window around this point on its Harris strength, so the phase correlation could be carried out to estimate the shift. This method suppressed the image-beundary without introducing truncating error, and it did the phase fitting simply by the first Fourier component. Experimental results validate the accuracy of shift estimation is improved greatly by introducing the Harris strength for scenes which contain prominent geometric points.%相位相关法是一种常用的图像配准方法,而直接基于傅里叶变换的快速图像配准方法(FDFA)使之具有亚像素级的配准精度,它需要根据图像内容细心选择参与相位拟合的频率分量,并在图像上施加窗口以抑制频域的图像边界效应,从而提高其偏移量估计精度.从边界效应抑制的角度出发,利用Harris角点量代替原始图像进行相位相关计算,与传统的对原始图像加窗的方法不同,该方法既抑制了边界效应,又避免引入截断误差.同时只用对其第一项频率分量进行拟合,而不需要进行频率项的选择,使相位拟合过程更简单.提取图像的Hard8角点并选择其中的几何特征点,对该点所对应的Harris角点量图区域施加圆形窗口;而后进行相位相关运算就能求出图像亚像素偏移量.实验表明,对于具有明显几何特征点的场景,所提方法使得偏移量的估计精度有明显提高.