改进极坐标的频域图像配准算法

A frequency-domain image registration algorithm using the improved polar transform

针对传统极坐标变换在频域配准中的问题,提出了一种基于改进极坐标的频域配准算法。先对参考图像和待配准图像分别进行傅立叶变换,将频谱信息映射至改进极坐标下。依次沿角度和极径方向投影,计算出图像间的旋转、缩放参数;再对待配准图像进行相应地旋转、缩放校正,根据幅度加权的相位差进一步得到图像间的平移量。当耗费的计算量大致相当时,与基于传统极坐标或伪极坐标变换的频域配准算法相比较,文中算法获得更高的图像配准精度。

The traditional polar transform usually suffers from the non-uniform sampling problem, which means that the low-frequency components are often over-sampled, while the high-frequency components are relatively under-sampled. Consequently, the inappropriate sampling rates will affect the registration accuracy, or else increase the computation cost vainly. To conquer the drawbacks mentioned above, we develops a novel frequency-domain registration algorithm using the improved polar transform. The reference image and the image to be registered are both carried out Fourier transform individually, and the corresponding spectrum images are sequentially mapped into the improved polar coordinate. Then projection operations are done along the angular and radius direction, respectively. As a result, the rotation and scale parameters between the two spatial images can be easily induced from the corresponding projection curves. Eventually, the shift parameters are retrieved with the weighted phase difference, after the inverse rotation and scale operations are implemented for the image to be registered. The experimental results show that the registration precision of our algorithm is much higher than the algorithm using the traditional polar transform or the pseudo-polar transform, while the required computation costs are almost equivalent.