新一代通用视频编码标准H.266/VVC:现状与发展  

The New-Generation Versatile Video Coding Standard H.266/VVC:State-of-the-Art and Development

作　　者：万帅[1,2] 霍俊彦 马彦卓[3] 杨付正 WAN Shuai;HUO Junyan;MA Yanzhuo;YANG Fuzheng(School of Electronics and Information,Northwestern Polytechnical University,Xi’an 710129,China;School of Engineering,Royal Melbourne Institute of Technology,Melbourne VIC3001,Australia;School of Electronic Engineering,Xidian University,Xi’an 710071,China)

机构地区：[1]西北工业大学电子信息学院,西安710129 [2]皇家墨尔本理工大学工程学院,澳大利亚墨尔本VIC3001 [3]西安电子科技大学通信工程学院,西安710071

出　　处：《西安交通大学学报》2024年第4期1-17,共17页Journal of Xi'an Jiaotong University

基　　金：国家自然科学基金资助项目(62171353,62101409);陕西省自然科学基础研究计划资助项目(2024JC-YBMS-463)。

摘　　要：相比于上一代标准,新一代通用视频编码标准(H.266/VVC)在同等质量下能够节省大约50%的码率,且适用于多种多样的视频应用场景。论文从H.266/VVC的关键技术出发,对标准的现状、实现和应用发展进行深入探讨。H.266/VVC沿用既往标准中的双层码流体系和混合编码框架,针对帧内预测、帧间预测、变换、量化、环路滤波等所有主要编码模块进行了技术革新,并为屏幕内容视频等应用提供了高效的专用编码工具。H.266/VVC标准目前已处于实用化阶段,官方参考软件VTM和开源编解码器VVenC/VVdeC是目前最具代表性的软件编解码实现。对H.266/VVC的性能分析可以看出:H.266/VVC针对高分辨率视频取得的编码增益更为突出;主要编码工具对性能的贡献通常以复杂度为代价,但也有部分编码工具在提升编码性能的同时可降低整体编码复杂度。H.266/VVC的硬件实现面临诸多挑战,发展明显滞后于软件实现,现有研究主要集中在对具体编码模块的硬件加速方面。H.266/VVC标准发布之后,下一代视频编码标准的发展目前仍围绕混合编码框架进行探索,聚焦在两大方向:超越VVC的增强压缩关注更为先进的、非神经网络的编码工具,基于神经网络的视频编码则探索采用神经网络的编码工具。除此之外,部分或完全跳出现有混合编码框架的端到端视频编码也在飞速发展,未来视频编码标准与神经网络结合成为趋势,但面临着计算资源依赖和稳定结构两方面的考验。Compared with the previous-generation standard,the new-generation versatile video coding standard H.266/VVC saves about 50%of the bit rate given the same quality and applies to a wide range of video application scenarios.The status quo,implementation,and application development of H.266/VVC are discussed in this paper from the perspective of its key technologies.H.266/VVC retains the dual-layer bitstream structure and hybrid coding framework of the previous standard while introducing technological innovations to all the major coding modules such as intra-frame prediction,inter-frame prediction,transformation,quantization,and loop filtering.Moreover,it provides efficient specialized coding tools for applications such as screen content videos.Currently,the H.266/VVC standard is in a practical stage,with the official reference software VTM and the open-source codecs VVenC/VVdeC serving as the most prominent software codec implementations.An analysis of the performance of H.266/VVC reveals that it achieves more notable coding gains for high-resolution videos.While some of the main coding tools contribute to improved performance,they may also increase complexity.Nevertheless,certain coding tools manage to enhance coding performance while reducing overall coding complexity.The hardware implementation of H.266/VVC faces many challenges,and its development lags behind software implementation.Following the release of H.266/VVC,the development of a next-generation video coding standard still focuses on the hybrid coding framework.There are two main directions:Enhanced compression in Beyond VVC concentrates on more advanced,non-neural-network-based coding tools,while neural-network-based video coding explores the use of neural-network-based coding tools.Furthermore,there is rapid progress in the development of end-to-end video coding that partially or completely deviates from the existing hybrid coding framework.In the future,the combination of video coding standards with neural networks will become a trend while facing the

关 键 词：H.266/VVC标准 视频编码标准 编码模块 编解码器 神经网络 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]