Research On Intra-Frame Of AVS-M And The Optimization Of Encoder

With the 3rd Generation and the rapid growth of multimedia service, the role played by multimedia communication has become increasingly important and essential in next generation communication system. Therein, video coding is the fundamental and kernel technique in emerging multimedia/video communication. AVS-M is the latest video coding standard developed by China for mobile application, which is the part 7 of domestic AVS (Audio Video coding Standard) series standard. AVS-M is designed to give a technical solution for a broad range of applications, such as interactive storage media, broadband video service, multi-media mail, long distance video surveillance, video conference, and video phone, etc. It is the video coding standard orienting next generation mobile communication in China.The design of AVS-M is based on conventional block-based motion-compensation hybrid video coding concepts. For the enhancement of the coding efficiency, AVS-M adopts new tools as followed: new intra frame prediction, variable block-size with seven block sizes in motion prediction, multiple reference picture, quarter-pixel accuracy for motion vectors, integer transform and loop deblocking filter.The intra-prediction method is analyzed in detail.It uses lagrange rate distortion optimization (RDO) technique to decide the best intra-coding mode in nine mode. The complex part-prediction mode selection is researched deeply, then two fast intra-prediction methods are given.A fast intra prediction mode selection algorithm is proposed. It uses spatio-temporal correlation of intra prediction modes and the information of edge direction in the current coding macro block and to fast determine the best mode with the RDO criterion. The another intra prediction is bi-directional (forward and backward) prediction.We found that the one-directional prediction results in identical prediction values for all samples in the same direction. However in a nature video frame, one sample usually has different value from its neighbors, even in a smooth region. Furthermore, the value of a sample lies highly likely among the values of its surrounding neighbors, and thus bi-directional prediction usually brings a better result than one-directional one. So the bi-directional prediction method is discussed and improved based on the idea proposed by Teng from Canada.After optimizing AVS-M encoder at algorithm level, we'll further optimize the computationally intensive modules in encoder using Intel's MMX/SSE/SSE2 instruction set and significantly speed up the encoder.The conclusions and directions for future research work are discussed in the last chapter of this thesis.