多视点视频编码论文：多视点视频编码技术研究
【中文摘要】近年来,随着信息技术的发展,通信与计算机图形学、计算机视觉、多媒体等技术的融合,使更具真实感的三维视觉享受和交互特性的多视点视频(Multi-view Video ,MVV)的实现成为可能。因此,多视点视频成为当前视频领域的研究热点之一。多视点视频是由处于空间不同位置的摄像机阵列拍摄同一场景得到的一组视频序列信号。随着摄像机数增加,多视点视频的数据量和冗余度也大幅度增加。为了存储和传输多视点视频,就必须对其进行高效的压缩。为此,ISO/IEC运动图像专家组(MPEG)和ITU-T视频编码专家组(VCEG)组成的联合视频组(JVT)发布了基于最新视频编码标准H.2/AVC的软件参考模型-JMVC(Joint Multi-view Video Coding)。在JMVC中,不仅在单个视点中利用帧内编码和运动估计去除空间冗余和时间冗余,而且在相邻视点利用视点间相关性进行视差估计去除视点间冗余。虽然JMVC获得了较高的编码效率,但这是以大量增加编码复杂度为代价的。因此,如何在保证视频编码质量和总比特率几乎不变的情况下,尽可能地降低编码复杂度对多视点视频编解码器走向应用至关重要。基于此,本文在两个方面对多视点视频编码算法进行了改进。一方面,本文对JMVC中基于分层B帧的参考预测结构(HBP)进行了分析。针对JMVC中采用的分层B帧预测结构编码复杂度高,随机访问性能较差等缺点,提出了一种改进的预测结构。所提出的预测结构对B视点中以前一帧作为其时间参考的帧仅采用时间预测,对所有P视点
的非关键帧均不进行视点间预测,并选取了合适的I视点位置,以减少结构简化带来的编码效率损失。实验结果表明,所提出的预测结构在保证编码效率损失不大的情况下,显著地降低了平均编码时间。同时,改进的预测结构也具有更好的随机访问性能。另一方面,本文在改进的预测结构中引入模式选择优化的方法。在保证不显著牺牲视觉质量的前提下,进一步降低计算复杂度。实验结果表明与JMVC中的参考预测结构和穷尽模式选择相比,经过模式选择优化和改进预测结构的联合编码在视频编码质量损失不大的情况下,极大地降低了编码复杂度。
【英文摘要】With the recent development of information technology, computer graphics, computer vision, and multimedia, 3D visualization and interactivity has become available. Consequently, Multi-view Video Coding (MVC) becomes a research hotspot in the video coding. These multi-view videos are acquired by using a set of cameras synchronously capturing the same scene but from different viewpoints. As the number of cameras increases, the amount of data and redundancy rapidly increase, too. In order to store and transmit these multi-view videos for the practical applications, efficient multi-view video coding (MVC) is highly desirable. To this end, the Joint Video Team (JVT) has developed a reference model, the Joint Multi-view Video Coding (JMVC), based on H.2/AVC video coding
standard. Although the coding performance of JMVC is good enough, but at the cost of very high computational complexity. Therefore, how to reduce the computational complexity while maintaining almost the same video coding quality is a key issue for any practical MVC codec.In order to reduce the
computational complexity and improve the temporal and spatial random access performance of hierarchical B pictures coding structure, which has been adopted as the basic coding structure in Joint Multi-view Video Coding (JMVC), an improved prediction structure is proposed in this paper. The frame in B-view which uses the immediate previous frame as its reference adopts only temporal prediction, and inter-view prediction is skipped in non-anchor frames in P-view, so that computational complexity is reduced and random access ability is improved. The position of I-view is also studied to minimize the loss of coding efficiency introduced. Experimental results have shown that compared to the hierarchical B pictures coding structure in JMVC, the proposed scheme achieves a remarkable reduction of encoding time on average with insignificant gain loss. Meanwhile, better random access performance has also been obtained.To further reduce the computational complexity, the proposed improved prediction structure is cooperated with mode
decision optimization in this dissertation. Experimental results have shown that compared with the reference prediction structure and exhaustive mode decision in JMVC, the adopted algorithm achieves a great reduction of computational complexity while maintaining almost the same video coding quality.
【关键词】多视点视频编码 预测结构 分层B帧 模式选择 视点间相关性
【英文关键词】Multi-view Video Coding Prediction Structure Hierarchical B Pictures Mode Decision Inter-view Correlation
【目录】多视点视频编码技术研究3-5
Abstract5-6
9-10
第一章 绪论9-17
论文摘要1.1 课题
研究背景与意义10-14
1.2 国内外研究概况和水平
1.3 多视点视频
第二
1.2.1 多视点视频编码12-14
的标准化过程14-16章 多视点视频编码研究17-1818-21
1.4 论文的章节安排16-1717-28
2.1 多视点视频的功能需求
2.2 匹配准则与多视点视频质量评价指标2.2.1 匹配准则
18-19
2.2.2 多视点视频质量
2.3
评价指标19-202.2.3 测试序列和测试条件20-21
多视点视频编码预测结构21-2723-26
2.3.1 分层B 帧预测结构
2.4 本
2.3.2 GOP 结构与视点预测结构26-27
章小结27-28第三章 预测结构的改进28-383.1 预测
结构的评价标准28-3131-34
3.2 JMVC 参考预测结构分析与改进
3.2.2 I 视点3.3.1 编码
3.4
3.2.1 参考预测结构分析32-34
3.3 实验结果与分析34-37
位置的选取34复杂度比较35-36本章小结37-38编码39-42
38-47
3.3.2 随机访问性能比较36-37
第四章 改进预测结构与模式选择优化的联合4.1 JMVC 中的运动估计和视差估计
4.2
4.1.1 JMVC 宏块模式选择算法流程41-42
42-4446-47
47-48
基于运动程度的模式选择算法44-47-5048-50论55
4.4 本章小结
4.3 实验结果与分析第五章 总结与展望
5.2 工作展望
5.1 论文总结参考文献50-54文
54-55
作者攻读硕士学位期间发表的
致
谢
