Data partition for wavefront parallelization of H.264 video encoder

This paper presents a new method for parallel processing of H.264 video encoder using data partition and task scheduling that fully exploits all data dependencies for maximal compression (Zhao and Liang). The new method achieves the optimal compression at a frame rate that increases approximately linearly as the number of parallel processing elements. This is a significant improvement over prior art parallel encoders for H.264 which invariably sacrifice data dependency and/or optimal coding mode. It is shown that the new method outperforms prior approaches in both encoding speed and compression efficiency. This paper also gives the relation between the number of parallel processing elements and the theoretical encoding time and the relation between the number of processors and the number of concurrently processed frames. Software simulation shows that this parallel processing method achieves the same compression quality as a sequential processing encoder, e.g., the JM series