Because motion estimation algorithm occupies 60~80% of the entire computation in image stabilization algorithm, and the difficulty increases with the improvement of image resolution and real-time stability of continuous image sequences, a GPU-based phase correction strategy for stabilization phase correction algorithm is presented. Based on mathematical models, a unified parallel architecture of image processor and pixel single-threaded mode are used, the phase of motion estimation overlapping composite structure is designed, improving the performance of the parallel thread synchronization. The computation time of parallel FFT is reduced. At the same time, change the scale of parallel threads, adjust the graphics processor storage, improve memory access performance data and motion estimation phase of concurrency, and estimate a stable rotation and translation etc. required for video in order to achieve fast and stable gray scale resolution of 1 k × 1 k purpose of continuous video. Experimental results show that the average time is about one frame stable 10ms, which effectively enhance the efficiency of video stabilization, and the possibility of image stabilization phase engineering applications.