The invention provides a motion parameter estimation method based on gray integral projection cross-correlation function characteristics. A horizontal moving motion model is adopted, and the method comprises the following steps that a target image is divided into N*N rectangular partitioning blocks with the equal size, gray integral projection is performed on each partitioning block, the variance of gray integral projection of each partitioning block is determined, R areas with the large variance can be selected as alternative areas, the cross-correlation operation is performed on gray integral projection of the alternative areas in two continuous frames of the target image, second derivatives of a cross-correlation function extreme point are calculated, weighted summation is performed on the variance of gray integral projection and the second derivatives of the cross-correlation function extreme point, good and poor factors of the alternative areas are obtained, the good and poor factors are arranged in a sort descending mode, the Q areas arranged in front are selected as the good-quality areas, local motion parameter estimation is performed on the obtained good-quality areas respectively, horizontal moving motion parameters in the direction of an axis X axis or an axis Y are obtained, and weighted summation is performed on the local motion parameters of the good-quality areas to obtain global motion parameters. According to the method, global motion parameters of an image with the low contrast ratio and the high resolution ratio can be effectively estimated.