传统的灰度投影算法是通过视频图像序列的像素值的灰度变化规律来获得图像序列帧间的全局运动矢量，然而该算法在灰度值单一，并且存在小运动物体时，稳像效果不佳，易造成误差。进而在深入分析传统灰度投影算法的基础上，提出了一种分区的梯度投影算法。该算法先对灰度图像进行预处理，继而将图像分成4个区域，若图像存在运动物体，此时可以剔除有运动物体的宏块，然后在每一个区域内用Sobel算子计算其水平、垂直梯度投影，进一步获得每个区域的局部运动矢量，最后采用均值方法得到全局运动矢量。实验结果表明，该方法在处理灰度值单一且存在运动物体的图像时，可以有效地提高精度，且通过分区的方法可以有效地降低运动物体的干扰，从而提高了算法精度。%The traditional gray projection algorithm obtains the global motion vector of inter-frames in image sequence by the gray pixel values of the video image sequence. However,the image stabilization effect of the algorithm is poor for the image with moving objects and single gray value. Based on analyzing the traditional gray projection algorithm in depth,propose an improved gradient projection algo-rithm. Firstly,the gray image is preprocessed with the Gauss function. Then the image is divided into four regions. If the image has mov-ing objects,so can remove the macroblock with the moving objects. Then,use the Sobel operator to calculate the horizontal and vertical gradient projection,further to obtain the local motion vector. Finally by average method,get the global motion vector. The experimental results show that the method for the image with moving objects and single gray value can improve the estimation accuracy of motion vec-tor. And it can effectively reduce the interference of moving objects by partitioning,which effectively improves the accuracy of the algo-rithm.
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