High-Accuracy Image Rotation and Scale Estimation Using Radon Transform and Sub-Pixel Shift Estimation
High-Accuracy Image Rotation and Scale Estimation Using Radon Transform and Sub-Pixel Shift Estimation
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DOI：
10.1109/access.2019.2899390
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发表时间：
2019
期刊：
影响因子：
3.9
通讯作者：
Takanori Fujisawa;M. Ikehara
中科院分区：
文献类型：
--
作者：
Takanori Fujisawa;M. Ikehara
图像的旋转和尺度估计是图像配准的基本任务。传统的估计方法使用对数极坐标变换和1D移位估计来估计旋转和尺度，而不管图像的移位。然而，该变换需要频率分量的内插，这导致估计误差。提出了一种基于Radon变换和亚像素位移估计的旋转和尺度估计算法。Radon变换可以独立于位移估计旋转，并且可以减少插值误差的影响。此外，使用相位分量的线性近似的子像素移位估计提高了1D移位估计的精度，并且实现了精确的旋转估计。实验结果表明，与对数极坐标变换相比，该方法具有更高的精度。
Rotation and scale estimation of images are fundamental tasks in image registration. The conventional estimation method uses log-polar transform and 1D shift estimation to estimate rotation and scale regardless of the shift of images. However, this transform requires interpolation of the frequency components, which causes estimation error. We propose a rotation and scale estimation algorithm based on the Radon transform and sub-pixel shift estimation. The Radon transform can estimate the rotation independent of the shift and can reduce the influence of interpolation error. In addition, sub-pixel shift estimation using a linear approximation of the phase component improves the precision of 1D shift estimation and achieves accurate rotation estimation. The proposed method was evaluated on test images, and the results demonstrate that the proposed method has higher accuracy compared with the log-polar transform.