Abstract:

The traditional electronic image stabilization approaches cannot be realized in real time. For this reason, we proposed a novel method based on SURF ( Speed Up Robust Features) registration algorithm. Additionally, CUDA(Compute Unified Device Architecture) programming and Kalman predictor are used for algorithm acceleration and real-time prediction. The proposed method extracts, selects and registers feature points based on CUDA parallel programming, and then obtains the motion vector between video frames. The Kalman predictor is used to predict the motion vector of the current frame, and then to realize the motion compensation as well as the real-time image stabilization. The simulation results show that the proposed algorithm can effectively remove the shake between frames, obtain perfect image stabilization effect, and deal with the question of real time process.

Key words: electronic image stabilizing, compute unified device architecture (CUDA) programming, speed up robust features (SURF) matching, Kalman predictor