针对运动背景下帧间稳像技术，提出了一种带运动矢量修正的灰度投影运动估计算法。采用该算法分别对当前帧和参考帧的行、列计算灰度投影序列；将当前帧投影序列局部分块，分别将每一分块与参考帧行、列投影曲线进行互相关计算，得到基于局部投影的行、列运动矢量集合；以分块区域的相关置信度为权系数衡量参数，计算每一分块的像素位移权值，从而计算某一方向帧间的加权运动矢量。实验结果表明：该方法可以使运动目标造成的影响只作用于其中若干个局部分块，而其他分块不受此影响，尽可能保证稳像的准确性。采用该方法稳像后的图像与参考帧图像的均方根误差(RMSE)值明显下降，与参考帧图像更加吻合。

As for the image stabilization of frame and frame under a complicated movement background, we present a motion estimation algorithm with motion vector modified by gray projection. First, we separately calculate grayscale projection sequences on the row and column of a current frame and a reference frame. Second, the projection sequences of current frame are divided into blocks. Each piece of block respectively performs a cross-relation calculation with the projection curves of rows and columns of the reference frame. Then, we can obtain the motion vector sets of rows and columns based on local projection. Finally, by using the confidence degree of block area as calculation parameters of weight coefficient, we calculate the weight of each piece of pixel displacement by the parameters to calculate the weighted motion vector in one direction. The experimental results show that this method can make the impact of moving target only on the one of the several local blocks and the other blocks are not affected. It ensures the best possible image stabilization accuracy. The Root-Mean-Square Error(RMSE) values obtained by image stabilization and reference images have decreased significantly, which shows the image stabilization by this method is more consistent with that of the reference image.