【作者】 袁涛；

【导师】 汪同庆；

【作者基本信息】 重庆大学 ， 仪器科学与技术， 2009， 硕士

【摘要】 H.264是由ITU-T视频编码专家组VCEG( Video Coding Experts Group)和ISO/IEC运动图象专家组MPEG ( Moving Picture Experts Group)共同制定的视频编码标准,这一编码标准可获得更高的编码效率,尤其是在低码率方面比MPEG-4有明显提高,适合低宽带、高质量网络视频应用的需要。但H.264在提高编码质量、减少码率的同时,却极大的增加了编解码运算的复杂度。通过对H.264编码部分的分析可以得出,运动估计是视频压缩编码中的核心技术之一,也是耗费时间最多的部分。在采用单参考帧和多参考帧预测的情况下,运动估计的运算量分别占整个编码过程运算量的60%、80%左右。因此,如何提高运动估计的效率,使运动估计算法搜索过程更健壮、更快速、更高效成为目前研究的热点之一。论文首先对H.264标准原理及运动估计部分算法进行了详细阐述,然后从以下三个方面对运动估计部分进行优化: (1)动态搜索范围算法,通过当前编码块运动矢量预测值来动态设置运动搜索的范围,从而减少所需搜索的点数。(2)固定模式快速运动估计算法,主要是在现有UMHexagonS算法的基础上进行改进,来进一步提高运算速度。(3)宏块分块模式的快速抉择,利用各种预测模式出现概率的差异及时、空相关性,缩小当前编码块所需计算的分块模式。经过充分的实验测试,改进后的运动估计算法在保证编码图象质量的同时,能显著减少运动估计的时间,从而加快编码速度。更多还原

【Abstract】 H.264 is the latest video coding standard, jointly developed by ITU-T VCEG (Video Coding Experts Group) and ISO / IEC MPEG (Moving Picture Experts Group). It can achieve higher coding efficiency than MPEG-4, especially in low bit-rate , and is more suitable for low-bandwidth, high-quality network video applications.But while improving the quality and reducing the bit-rate, H.264 increased the codec complexity of computation dramatically. After extensive analysis of H.264, motion estimation is one of the core technology, but also the most time-consuming part. For example , in a single-reference frame and multi-reference frame prediction, the computation of motion estimation respectively account for about 60%, 80% of the total computation . Therefore, how to improve the efficiency of motion estimation, and make the search process more robust, faster and more efficient has become a focus of current research.This thesis introduces the protocol and principle of H.264 and the algorithm of motion estimation in detail firstly, then optimizes the algorithms of the motion estimation from the follow three aspects to accelerate the process of motion estimation. (1) Adaptive Dynamic Search Range Algorithm, determining adaptively the unsymmetrical search range in negative/positive direction of horizontal/vertical axis according to the Predictive Motion Vectors set to reduce the search points. (2) Fixed-mode Fast Motion Estimation Algorithm, mainly focus on the improvements of the existing UMHexagonS algorithm, to further enhance the computational performance of Motion Estimation. (3) Fast Mode Selection Algorithm of Macroblock, utilizing the probability distribution of the various modes and Spatio-Temporal correlation of macroblocks to reduce the number of modes required to compute. Extensive experiments show that these algorithms can achieve significant computational reduction of motion estimation, compared with the previous algorithms in Joint Model (JM) , while maintaining almost the same quality of reconstructed pictures.更多还原