Aiming at the engineering problems such as the blind spots of large and medium vehicles during driving and parking and the difficulty of multi-channel real-time video stitching, we design a safe driving assistance system based on multi-channel cameras as well as FPGA and GPU platforms. FPGA is responsible for preprocessing, including image data acquisition and parameter transfer, and parallel acceleration of stitching algorithms is enabled on GPU. Besides, automatic calibration of multiple cameras is achieved with the optimized algorithm, and a fusion parameter table was generated to acquire accurate image registration and fusion. The experimental results prove that the system can adapt to the real-time stitching of multi-channel fish-eye cameras, and the stable stitching speed on TX2 can reach 33 fps.