Research And Implementation On The MFHS Algorithm Based On H.264

In today’s society, along with the sharp increase of network technology and digital technology,, the multimedia information has become an important carrier for people to obtain information. While the video information is a significant part of multimedia information:the redundancy of the video data is quite big, the video image quality after compression processing intuitively determines the quality of the multimedia service, therefore, the study and research of the video encoding is an extremely popular topic in the field of information technology.Among the H.264, the motion estimation has a direct impact on the efficiency and quality of the video data compression encoding. However, the motion estimation is the link that the operation is quite complicated and the consuming time is much more in the video compression, according to statistics, only the calculation of the motion estimation already accounts for half in the entire video data compression encoding process. Therefore, the effective motion estimation algorithm has immeasurable practical significance in the aspects of improving video data compression encoding efficient.In the first three chapters, the text detailedly describes the development of the basic principles of video compression coding technology. Then systematically introduces the H.264standard, afterwards presents the basic principle of motion estimation, the evaluation standard of block matching motion estimation search algorithm. Later, learn and research several classic motion estimation algorithm, analysis their search steps and strategies. Finally, focus on learning UMHexagonS algorithm, proposes a new algorithm-MFHS algorithm. The MFHS algorithm mainly includes three steps:Firstly, the using of four prediction vectors to search the initial point; Secondly, the using of multi-level large flat hexagonal grid point search method to capture irregular movement point; Lastly, the using of predictable flat exagonal template to complete accurate search. The new algorithm is effective in reducing the search time and the complexity of the algorithm. Analysis the performance of before and after, the results show that the new algorithm can greatly save the motion estimation time under the basically remain unchanged of coding performance, thus save coding time and further improve the coding efficiency.