针对全局运动估计难以同时取得有效性和实时性的难题，结合限制型1比特变换法(constrained one-bit transform, C-1BT) 和自适应十字搜索法提出一种快速准确估计全局平移运动的方法. 该方法改进传统的C-1BT方法，利用自适应门限构造模板图像，并在提取图像的低比特面和模板图像时均提前判定零运动矢量区域. 根据图像间相似性测度可代表运动趋势强度这一原则设置自适应门限，选择一定运动幅度范围内可靠的宏块. 仿真结果表明，改进的自适应十字搜索法更充分地利用了时间和空间的有效性，在保证精度的同时极大地减少了搜索点数量.

 Considering the difficulty in achieving effectiveness and real-time property simultaneously in the global motion estimation, and combining the bit-plane method and ARPS, an accurate approach for estimating the global translational motion is proposed. It improves the traditional C-1BT method by setting an adaptive threshold to construct the mask image. Early determination of zero motion vector areas is achieved, along with twice extraction of low bit planes. The similarity measures between images can represent motion intensity.As such, by selecting a sub-region of the similarity measures within a certain range, these regions can better represent the global motion trends as compared with other regions. Finally, the improved ARPS approach takes full advantage of space-time correlation. Simulation results show that the proposed approach can increases accuracy and reduces the amount of computation.