针对视频图像运动检测问题，提出了一种结合空域灰度投影和频域相位相关的亚像素图像配准方法。首先，采用灰度投影算法在空域对运动图像进行粗配准，即在图像行和列方向上计算图像灰度投影特征数据，根据灰度相关函数最小化准则，估计像素级运动量; 然后，在经过粗配准的两幅图像中心选取尺寸相同的区域，进行快速傅里叶变换，在频域采用扩展的相位相关算法对图像进行精确配准。该方法利用图像的功率谱信息，减少对图像内容的依赖，运用基于最小二乘的曲面拟合法，实现亚像素图像配准参数估计，具有从粗到精的特点，有效提高了图像检测精度。文中最后对样本图像进行了图像配准对比实验，结果表明，该方法可以检测0.01 pixel的运动量， 最大配准误差为0.004 8 pixel。

To resolve the problems existed in the estimation of motion in video sequences, a novel method combining the gray projection in a spatial domain and the phase correlation in a frequency domain was proposed. Firstly, the gray projection algorithm was adopted to coarsely register images to entire pixel accuracy, which calculates the gray correlation function for the spatial domain in row and column orientations and obtains the pixel-level motion vector between two sequential images by comparing correlation characters. Then, the phase correlation algorithm was adopted to refinedly register images to sub-pixel accuracy, which uses power spectrum information of images to decrease the image dependence. Furthermore, the fitting method of paraboloid surface based on least-square was used to fulfill the estimation of image displacement parameters. To verify the algorithm experimentally, some samples were simulated. The results show that this method can detect the displacement parameters accurately and efficiently, and can offer the image displacement in a accuracy of 0.01 pixel and the maximum registration error less than 0.004 8 pixel.