分布式视频编码的边信息融合与重构-通信与信息系统专业论文.docxVIP

第 第 II 页 的下一个比特值，并进一步利用预测得到的比特值修改重构概率密度函数。 该方案结果优于现有的单一重构概率密度函数性能，使得能在传输较少比 特平面时提高重构 Wyner-Ziv 帧的 PSNR 和主观质量。 此外，对于分布式多视点视频编码，本文则提出了基于条件随机场模 型的时间边信息、视间边信息融合方案。普通的边信息融合方案寻找时间 边信息中突变的运动矢量，并将相应的视频块用视间边信息替代。这一方 法是以块为单元的，容易在融合的边信息中产生不平滑的块边缘。本文通 过为条件随机场定义特征函数，训练出每个格点(像素)位置上重构 WZ 帧(前 一帧)、时间边信息、视间边信息三者之间的权重关系，根据训练出的权重 系数，进一步推断当前标签，从而得到最终边信息。该方法将视频帧像素 间的空间相关性引入到条件随机场模型中，能够有效地识别出时间边信息 中运动突变的区域，并将这些运动突变区域用视间边信息中的相应区域代 替。实验结果显示，该融合方案在率失真性能方面要优于现有的边信息融 合方案。 关键词：分布式单视点视频编码，重构概率密度分布，分布式多视点视频 编码，时间边信息，视间边信息，条件随机场，边信息融合 第 第 III 页 Side Information Fusion for Distributed Multi-view Video Coding ABSTRACT Distributed Video Coding (DVC) is a new concept based on Slepian-Wolf lossless and Wyner-Ziv lossy compression theories, where several sources with the same distribution are independently encoded and jointly decoded. Different from conventional video coding technologies: conventional video coding technologies exploit correlations at the encoder side, thus making the encoding complexity 5~10 higher than decoding complexity. Conventional video coding applies well to video broadcasting, video on demand (VOD) and video disk storage, etc; while DVC takes advantage in low encoder complexity, low power consumption and strong error resilience. Thus, DVC has its application in wireless video terminator such as wireless video monitoring system and video sensor network which have limited computation ability, storage capability and power consumption. Distributed Multi-view Video Coding (DMVC) can be regarded as a extension of DVC. Different from DVC which has only temporal side information, there exist side information generated from inter-view direction as well in DMVC. Although the quality of temporal side information is better than that of inter-view side information, from local aspect, inter-view side information is better than temporal one where the motion is high. The task of side information fusion is to find the better side information in the same area and select it as the final sid