RTP payload format for H.264/SVC scalable video coding

The scalable extension of H.264/AVC, known as scalable video coding or SVC, is currently the main focus of the Joint Video Team’s work. In its present working draft, the higher level syntax of SVC follows the design principles of H.264/AVC. Self-contained network abstraction layer units (NAL units) form natural entities for packetization. The SVC specification is by no means finalized yet, but nevertheless the work towards an optimized RTP payload format has already started. RFC 3984, the RTP payload specification for H.264/AVC has been taken as a starting point, but it became quickly clear that the scalable features of SVC require adaptation in at least the areas of capability/operation point signaling and documentation of the extended NAL unit header. This paper first gives an overview of the history of scalable video coding, and then reviews the video coding layer (VCL) and NAL of the latest SVC draft specification. Finally, it discusses different aspects of the draft SVC RTP payload format, in- cluding the design criteria, use cases, signaling and payload structure.

SST-V:A Scalable Semantic Transmission Framework for Video

The emerging new services in the sixth generation(6G)communication system impose increasingly stringent requirements and challenges on video transmission.Semantic communications are envisioned as a promising solution to these challenges.This paper provides a highly-efficient solution to video transmission by proposing a scalable semantic transmission algorithm,named scalable semantic transmission framework for video(SST-V),which jointly considers the semantic importance and channel conditions.Specifically,a semantic importance evaluation module is designed to extract more informative semantic features according to the estimated importance level,facilitating high-efficiency semantic coding.By further considering the channel condition,a cascaded learning based scalable joint semanticchannel coding algorithm is proposed,which autonomously adapts the semantic coding and channel coding strategies to the specific signalto-noise ratio(SNR).Simulation results show that SST-V achieves better video reconstruction performance,while significantly reducing the transmission overhead.

Multipoint videoconferencing with scalable video coding

We describe a system for multipoint videoconferencing that offers extremely low end-to-end delay, low cost and complexity, and high scalability, alongside standard features associated with high-end solutions such as rate matching and per- sonal video layout. The system accommodates heterogeneous receivers and networks based on the Internet Protocol and relies on scalable video coding to provide a coded representation of a source video signal at multiple temporal and spatial resolutions as well as quality levels. These are represented by distinct bitstream components which are created at each end-user encoder. Depending on the specific conferencing environment, some or all of these components are transmitted to a Scalable Video Conferencing Server (SVCS). The SVCS redirects these components to one or more recipients depending on, e.g., the available network con- ditions and user preferences. The scalable aspect of the video coding technique allows the system to adapt to different network conditions, and also accommodates different end-user requirements (e.g., a user may elect to view another user at a high or low spatial resolution). Performance results concerning flexibility, video quality and delay of the system are presented using the Joint Scalable Video Model (JSVM) of the forthcoming SVC (H.264 Annex G) standard, demonstrating that scalable coding outper- forms existing state-of-the-art systems and offers the right platform for building next-generation multipoint videoconferencing systems.

Cooperative Caching for Scalable Video Coding Using Value-Decomposed Dimensional Networks

Scalable video coding(SVC)has been widely used in video-on-demand(VOD)service,to efficiently satisfy users’different video quality requirements and dynamically adjust video stream to timevariant wireless channels.Under the 5G network structure,we consider a cooperative caching scheme inside each cluster with SVC to economically utilize the limited caching storage.A novel multi-agent deep reinforcement learning(MADRL)framework is proposed to jointly optimize the video access delay and users’satisfaction,where an aggregation node is introduced helping individual agents to achieve global observations and overall system rewards.Moreover,to cope with the large action space caused by the large number of videos and users,a dimension decomposition method is embedded into the neural network in each agent,which greatly reduce the computational complexity and memory cost of the reinforcement learning.Experimental results show that:1)the proposed value-decomposed dimensional network(VDDN)algorithm achieves an obvious performance gain versus the traditional MADRL;2)the proposed VDDN algorithm can handle an extremely large action space and quickly converge with a low computational complexity.

Streaming and congestion control using scalable video coding based on H.264/AVC

This paper presents a streaming system using scalable video coding based on H.264/AVC. The system provides a congestion control algorithm supported by channel bandwidth estimation of the client. It uses retransmission only for packets of the base layer to disburden the congested network. The bandwidth estimation allows for adjusting the transmission rate quickly to the current available bandwidth of the network. Compared to binomial congestion control, the proposed system allows for shorter start-up times and data rate adaptation. The paper describes the components of this streaming system and the results of experiments showing that the proposed approach works effectively for streaming video.

Fast mode decision for Hierarchical-B pictures in scalable video coding

To decrease the computational complexity of adaptive inter-layer prediction and improve the encoding efficiency in sealable video coding, a mode decision algorithm is proposed by exploiting the part of used candidate modes of the co-located reference macrobloeks for Hierarchical-B pictures. This scheme reduces the amount of the candidate modes to generate a dynamic list for the current encoding macroblock according to the statistical information derived from the co-located reference macroblocks in different temporal levels. The experimental results show that this fast algorithm reduces approximately 31% encoding time on average with the negligible loss of encoding performance.

A complexity-scalable software-based MPEG-2 video encoder

With the development of general-purpose processors (GPP) and video signal processing algorithms, it is possible to implement a software-based real-time video encoder on GPP, and its low cost and easy upgrade attract developers' interests to transfer video encoding from specialized hardware to more flexible software. In this paper, the encoding structure is set up first to support complexity scalability; then a lot of high performance algorithms are used on the key time-consuming modules in coding process; finally, at programming level, processor characteristics are considered to improve data access efficiency and processing parallelism. Other programming methods such as lookup table are adopted to reduce the computational complexity. Simulation results showed that these ideas could not only improve the global performance of video coding, but also provide great flexibility in complexity regulation.

Trade-off Optimization for Scalable Video Coding Streaming in Relay-Based OFDMA Networks

To achieve an optimal trade-off between video quality and energy efficiency in the uplink streaming of multi-user Scalable Video Coding (SVC) videos in relay-based Orthogonal Frequency Division Multiple Access (OFDMA) cellular networks, a cross-layer design framework that jointly selects the Transmission Policy (TP) for SVC video frames, assigns OFDMA subcarriers, and allocates power for each subcarrier is proposed. We apply the dual decomposition method to the problem, and obtain a TP selection subproblem for each SVC video adaptation and a resource allocation subproblem of Joint Subcarrier, Relay and Power Allocation (JSRPA). A second level of dual decomposition is used to divide the JSRPA problem into independent subcarrier subproblems. The proposed Crosslayer Trade-off Optimization (CTO) algorithm is sub-distributed with significantly low complexity. A performance evaluation with typical SVC video traces demonstrates that the proposed algorithm is able to converge and efficiently achieve the optimal trade-off between the video quality and energy consumption at the MSs for uplink SVC streaming.

The Performance of MANET Routing Protocols for Scalable Video Communication

Mobile Ad-hoc Networks (MANETs) operate without infrastructure where nodes can move randomly. Therefore, routing in MANETs is a challenging task. In this paper we evaluate the performance of three important MANET routing protocols: Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR) and Optimized Link State Routing (OLSR) when employed to forward scalable video contents. AODV and DSR are reactive protocols in that routing paths are established once needed. On the other hand, OLSR is a proactive routing protocol where routing information is exchanged and maintained continuously. The goal of the performance evaluation in this study is to assess the performance of AODV, DSR and OLSR in communicating scalable video contents. In the simulation part of this paper, a real video sequence is communicated where the characteristics and quality of the video decoded at receiver nodes are evaluated. NS2 along with extensions and other evaluation frameworks have been used to assess the performance of the MANET routing protocols when used for scalable video communication. The framework allows starting from a raw video that is encoded, packetized, transmitted through a network topology and collected at receiver to be decoded, played, and evaluated. Delay and timing constraints are taken into consideration when decoding the received video packets.

Scalable Compression Algorithm for Video Monitoring System

A layered compression algorithm is presented which delivers spatial scalable encoded bit streams for remote video monitoring system. The complexity of the algorithm is modest and is well suited to real time implementation. Based on the layered compression algorithm, a codec system model is established. High-speed video compression can be realized with parallel data compression in this codec system. For image reconstruction, a prediction method using two nearest pix points is presented.

D2D网络中基于SVC视频流缓存的跨层网络编码重传方案

为了降低基站重传视频流的完成时间,针对视频流业务设计了一种D2D网络中基于可伸缩视频编码(Scalable Video Coding, SVC)的视频流缓存跨层网络编码重传方案。该方案首先采用SVC对视频流进行编码以应对终端处理能力的差异性,引入跨层网络编码搜寻最大独立集选取最佳的传输以及编码调度,减少完成时间。其次,针对多协作重传设备间的干扰问题,设计了最佳的资源调度算法,在给定发送设备集的前提下迭代优化设备的发送功率,在不增加完成时间的同时优化系统的吞吐量。仿真结果表明,所提出的方案能够有效地降低完成时延,减少重传次数,增加系统的弹性。

基于SVC的P2P流媒体系统研究综述

根据数据传输系统架构的不同,将基于SVC的P2P流媒体系统分为tree型、混合型和mesh型三类;针对这三种类型研究进行深入调研,对现有关键技术进行总结,并指出当前工作的不足及未来的研究方向。其中mesh型系统中的关键技术是介绍的重点。

一种面向SVC的码率控制算法

H.264/AVC可伸缩性扩展视频编码系统(JSVM)提供了一种可伸缩视频编码(SVC)的解决方案,然而它本身并没有提供一种有效的码率控制算法.文中基于JSVM的分层预测结构,提出了一种全新的码率控制算法.首先在码率分配方面,考虑到分层B帧预测(或运动补偿时间域滤波(MCTF))结构,给出一种分层的码率分配方案;然后,针对不同类型和不同时间分解层各自的统计特性,分别为它们设计了不同的率失真(R-D)模型.实验结果表明,文中算法能够有效地控制码率,使得目标码率跟实际产生码率之间的偏差最大不超过2%;同时文中算法较大地提高了解码图像的质量,使得峰值信噪比(PSNR)在低码率端可提高1dB;另外,JSVM是通过不断调整量化参数(QP)使得实际产生的码率逐次逼近目标码率,较之这种尝试型的码率控制算法,文中基于模型的码率控制是在一次编码中产生最终的目标码率,从而大大降低了计算复杂度.

基于网络编码的SVC高效传输系统

为了同时提高网络中视频的传输效率和质量,提出了一种可分级视频编码(SVC)视频鲁棒性传输系统方案,并提出了该系统特性的描述方式.将随机线性网络编码技术和SVC技术相结合,得到了视频系统中视频流打包、传输和延迟特性的表达式,并分别说明了提高重建图像质量的数据包模型、码流组织方式和满足不同延时需求的码流传输方法.仿真结果表明,提出的算法可以有效提高视频的传输质量和效率.研究结果可以用于实际SVC视频传输系统的设计.

一种面向视频传输的SVC码流排序方法

该文提出了一种适用于传输的可分级视频编码码流的排序方法。该方法通过对码流的合理选择和对失真的高效近似计算,优先传输率失真性能较好的可分级码流,从而提高了重建图像的质量。该文建立了用于划分复合可分级码流的状态模型,推导出了可分级码流失真的近似计算公式,在一定带宽限制下,采用率失真优化的方法对可分级码流进行排序。仿真结果表明该方法能提高视频流重建图像质量。

针对样品视频的H.264空域SVC快速模式决策算法

在电子显微镜等大型科学仪器样品图像远程实时传输中，为了解决其网络适应性问题，采用IPPP结构的H．264空域SVC压缩样品视频。针对SVC模式决策的高计算复杂度问题，提出了一种快速模式决策算法。该算法精简了预测模式，并将其划分为不同的模式集，针对各模式集设计了自适应提前退出阈值及阈值比较策略，以尽快结束模式决策。对不同仪器样品视频的测试表明，该算法与参考算法相比，在PSNR和比特率保持相近的情况下，编码时间可减少73％-83％。

一种基于缩减栅格算法的SVC联合信源/信道编码方法

针对H.264/AVC可分级编码扩充标准（SVC）,本文提出了一种联合信源/信道编码（JSCC）的视频传输方法.该方法采用一种新型的缩减栅格算法与拉格朗日优化技术对SVC数据与差错控制保护级别进行最优分配.本文提出的缩减栅格算法采用疏散式栅格结构,实行依层计算与缩减队列的策略,计算效率比同类高效算法提高了约20~50倍.大量仿真数据表明,采用本文高效算法的JSCC方法在各种信道条件下达到同类方法相同的优化性能.

基于OpenFlow的SVC流媒体时延自适应分级传输方法

针对当前互联网流媒体传输的时延敏感性问题,提出一种基于OpenFlow的SVC(scalable video coding,可分级视频编码)流媒体时延自适应分级传输方法,该方法有效结合SVC流媒体可分级和OpenFlow灵活可编程的特性,在网络带宽受限和链路拥塞的复杂网络环境下,通过构建基础层和增强层2个独立路由,实现了动态网络下SVC流媒体分级自适应高效传输。仿真结果表明,该方法在提升SVC流媒体传输效率和质量,改善用户体验方面有重要作用。

基于SVC分层匹配度的异构网络节点选择算法

随着移动互联网和三网融合的兴起,网络带宽及终端异构性造成所选节点视频和请求节点的终端能力不匹配。为此,提出一种基于可扩展视频编码(SVC)分层匹配度的节点选择算法。在异构网络背景下,综合考虑节点带宽和链路往返时延,将SVC分层层数和网络接入类型相结合。实验结果表明,与随机选择算法相比,该算法使得所选节点的SVC视频分层数与请求节点终端处理能力有较高的匹配度(固网、无线、3G接入网络类型所对应的匹配度分别为77.8,72.2,88.9),并且具有较高的终端平均服务能力(PC为110、笔记本为78.3、手机为38.3)。

H.264/SVC的RTP封装算法及其应用

可伸缩视频编码(Scalable Video Coding,SVC)一般采用实时传输协议(Real-time Transport Protocol,RTP)保证视频数据流的实时传输和质量监测。在分析SVC码流结构和RTP协议的基础上实现了H.264/SVC视频数据的RTP封装算法,提出基本层与增强层分离的方法用于模拟可伸缩视频流在模拟测试环境中的传输,提出基于RTP封装的差错隐藏方法解决质量增强层数据丢失问题。实验结果证明了封装算法的有效性、标准兼容性和可扩展性。