基于非均衡差错保护的信源信道联合编码.pdf

摘 要 I 基于不等差错保护的信源信道联合编码基于不等差错保护的信源信道联合编码 摘 要 摘 要 香农的信源编码和信道编码分离理论所提出的达到最优编码性能是基于以下这两个假设，即信源编码和信道编码的码子可以无限长和无限复杂度这在实际应用中是做不到的，分离理论实际上限制了系统达到更优的性能由此，人们开始着眼于信源信道联合编码，其基本思想是综合地考虑信源和信道的特点，采用最优化的设计方法来提供对信息传递更好的错误保护以及更高的带宽利用率非均衡错误保护（UEP）是联合信源信道编码的一个研究方向人们注意到对于某些信源在通信系统中传输的比特流的各个部分有着不同的重要性， 由此引出了以不同等级来保护信号的不同部分视频通信是一种允许失真存在的业务，而且信息自身有着内在的重要性分布不均衡的特性， 视频编码的不同部分对 QoS 的要求不同，对重建的贡献也不同，结合这种图像和视频数据的内在特性，设计联合信源信道编码使得传输质量能尽可能地提高 本文综合近年来基于非均衡差错保护的联合信源信道编码方面的主要研究工作，成果以及重点和热点，对目前的 UEP 方法进行了比较细致的分类及总结并且对基于 GOP 的非均衡差错保护方法进行了比较深入的分析， 总结出了一些需要解决的问题： (1)如何对视频数据的重要性进行界定(2)需要多强的信道码进行保护。

在此基础之上分析了 H.264 标准代码中所使用的差错掩盖方法，即帧内编码宏块所采用的插值预测方法和帧间编码宏块所采用的宏块拷贝方法， 以及这两类差错掩盖方法与信道失真的关系给出这两类宏块的信道失真估计方法其次分析了视频通信中的差错扩散效应对信道失真的影响， 并且考虑了 H.264 中所使用的非线性环路滤波器的作用， 由此建立了一个由信道差错和差错扩散效应两部分所组成的信道失真估计模型 仿真实验显示我们的模型能较为精确的估计视频通信中的信道失真 在上述工作的基础上 我们建立了一个以达到信道失真最小为目标的信道码码率分配模型由于该模型不满足传统的求解优化问题方法的约束条件， 我们摘 要 II 采用遗传算法求解最优信道码码率分配方法 针对遗传算法应用于我们的问题做了收敛性分析并且确定了一些重要参数在实验仿真与分析部分，我们利用了H.264 标准从码率分配结果来看，由于我们的模型综合了差错掩盖、视频序列本身的运动特性和统计特性因此，一个 GOP 中位置靠后的帧也可能获得较强的信道码保护除此之外，我们针对两类不同信道失真预测结果的序列所得到码率分配结果进行了分析，得出了信道失真曲线较平滑的序列，其码率突变的情况较少的结论。

在系统性能分析中，实验结果显示我们的算法相对于现有的非均衡差错保护方法和均衡差错保护方法有较好的性能 特别在信道条件较为恶劣的情况下，我们的系统比均衡差错保护能获得 3-4dB 的性能提升 关键词关键词：H.264，非均衡差错保护，信源信道联合编码，差错掩盖，遗传算法, RS 码 ABSTRACT III Joint Source and Channel Coding based on Unequal Error Protection ABSTRACT Shannon's theory that source coding and channel coding can be optimized separately is based on the following two assumptions. That is the source codes and channel codes could be infinite length and the coding process could be unlimited complexity. These two assumptions are impractical. In fact, the “Separate Theory“ restricted the system to get optimal result. Thus, people began to lay their eyes on joint source and channel coding (JSCC) to design better systems. The basic concept of JSCC is considering the characteristics of source and channel synthetically to obtain an optimal method which could provide better error protection for information communication and more efficient bandwidth usage. Unequal error protection (UEP) is one branch of JSCC. People notice that the different parts of coded source stream are of unequal importance. The observation leads to the idea of UEP which means providing scaled protection for different parts of the source signal. For instance, video communication is an error tolerance service. The QOS of different parts of coded video streams are different since the importance distribution of video streams is not uniform. According to the interior characteristics of coded video data, we could design joint source and channel coding system to improve the system's performance. In this dissertation, we first integrated the works of joint source channel coding based on UEP in recent years and give a catalog of the work of JSCC. Then we analyze the method of UEP based on GOP in video communication and conclude some problems need to be solved: (1) How to make judgments on the importance of the data encoded by video compression system? (2) How to make a decision on the code rate of channel codes? To solve these problems, we analyze the error concealment method utilized by H.264 and construct a channel distortion estimation method. That is the pixel interpolation prediction method used by intra-frame coded ABSTRACT IV macro-blocks and “copy macro-blocks” method used by inter-frame coded macro-blocks. Furthermore, the approach takes into account the error propagation problem of video communication and considers the influence of the non-linear in-loop filter used by H.264. After that, we construct a channel rate distortion model composed by two parts which are caused by channel error and error propagation. The experiments’ results demonstrate that our model is of high efficiency. On the basis of previous analysis, we construct a channel rate allocation model for the purpose of obtaining the minimum channel distortion. Since our problem doesn’t satisfy the constraints of the traditional methods which are used to solve optimization problems, we choose Genetic Algorithm to get the optimal channel code rate allocation result. Combined with the property of Genetic Algorithm, we analyze the convergence property of our problem and set value of some important parameters. In our experiment, we utilized H.264 standard. From the result of channel code rate allocation results, we could notice that our model combined with error concealment property, the moving property of original sequence. So the experiments’ results tell us that the frames which are in the tail position might be protected by more robust channel code. Besides that, we analyze the channel code rate allocation results of sequences of different kind and conclude that the smoother the channel distortion curve is the less mutation the channel code rate allocation curves are. Experiments show that, compared with existed approach and equal error protection method, our rate allocation method effectively improves the system performance. Esp。