无线上行视频流的跨层容错传输方法

如何通过资源受限的移动通信终端提升无线上行视频流的抗误性能是亟待解决的重要问题。通过不同通信层次的联合调度,提出了一种跨层容错传输方案。移动通信终端的网络层代理首先利用容错包调度为视频流的延时约束帧集合提供重要性分类,随后该终端的链路层代理利用无线链路单元的优先级调度实现选择性重传。在调度延时与传输带宽限制下,跨层容错传输能够将突发错误转移到延时约束帧集合的低优先级视频数据中,从而在突发易错传输环境中实现了无线链路单元粒度的渐进式传输和平稳退化。     

基于GA-BP的实时视频通信自适应前向纠错码

针对在动态的网络环境中,实时视频在基于数据报协议的传输中遇到大量丢包的问题,提出了一种基于遗传算法改进的BP神经网络自适应前向纠错码的方法。该方法通过设计自适应的前向纠错编码来恢复丢失的数据包。首先,设计一个基于帧级别的前向纠错的框架,主要包括视频编码解码器、RS前向纠错码编解码模块和前向纠错码冗余度计算模块,用来模拟一般视频传输的环境;然后,设计GA-BP模型,将其应用到RS-FEC的冗余度计算,实现一种帧级不均等的保护方案;最后,基于GE信道模拟网络,生成丢包数据,训练离线模型,进行实验验证。实验结果表明,相比StaticRS和DeepRS,所提方法能够在较低冗余度下较高地恢复丢失的数据包,得到更高质量的视频。     

场景切换视频自适应帧间码率控制

针对视频帧中可能出现的大量场景切换,提出一种基于非连接点的场景切换检测算法,提高编码性能,该场景检测算法复杂度低,在运动估计的同时,完成视频场景切换检测。场景切换将导致GOP(group of pictures)长度的变化,并可能出现GOP长度太短的情况。提出改进的自适应GOP时域滤波技术,避免由于GOP太短引起的编码性能下降。针对视频场景切换检测分割出的不同长度的GOP,提出一种基于率失真模型的帧间码率控制算法,利用视频的失真与码率及视频帧复杂度的关系,对帧间码率分配进行优化,提高重构视频帧的总质量。实验结果表明,基于场景检测的自适应帧间码率控制算法能够获得较好的编码性能。     

一种鲁棒灵活的非平衡多描述视频编码和传输方案

在网络上传输的视频经常因为丢包而影响终端接收到的视频的质量.由于现有的视频编码器通常使用预测编码技术来减少时域冗余提高压缩率,所以一个包的丢失都会引起错误的传播,直到解码器收到帧内编码的帧为止.针对这个问题,文中提出一种灵活鲁棒的非平衡多描述编码和传输方案.其编码器借助不同描述间的"同步帧",能够迅速从包丢失中恢复解码,并保证终端视频的连续播放;同时,该方案能够灵活适应多路径传输和单路径传输两种情况.文中还研究了单路径传输时不同描述间的码率分配问题,并提出一种近似最优的快速码率分配方案.实验结果充分验证了文中提出的非平衡多描述编码和传输方案的有效性、鲁棒性和灵活性.     

一种MPEG-4 FGS流媒体自适应传输系统

针对MPEG-4FGS流媒体提出一种质最自适应传输系统,采用3种质量平滑机制,即GOP质量平滑、帧质量平滑和FEC差错控制,保证在丢包情况下的连续GOP以及每个GOP内连续帧的质量稳定。模拟结果表明,自适应传输系统能和Internet丢包环境下平滑连续GOP的质量和GOP内连续帧的质量。     

一种MPEG-4视频精确认证方案及实现

在MPEG-4视频中图像帧数量巨大,但帧组(GOP)的关键帧(第一帧)——Ⅰ帧图像屈指可数,数据量少。目前的视频认证方案尚不能检测突发的位错误,在细节区恢复被篡改的像素的精度也不能令人满意。为此,本文提出并实现了一种MPEG-4视频精确认证方案,通过对I帧像素进行汉明码编码,结合环面自同构和位旋转,进行篡改证明。实验表明,该方案能有效消除突发的位错误,进行像素级别的完整性认证,篡改定位效果好,恢复精度高,对精确认证具有重要的现实意义。     

基于SVC的空域增强层帧级错误掩盖算法

基于SVC空域增强层宏块编码模式的特点,提出一种增强层帧级错误掩盖算法,综合利用层间预测信息和时域直接模式TD下的运动信息,预测丢失帧中的宏块是否采用TD模式编码运动信息。对于符合判决条件的宏块,使用TD模式来产生其运动矢量,以提高运动矢量恢复的精确度,从而提升丢失帧的错误掩盖效果。实验结果表明,与原JSVM算法相比,该算法以很小的运算复杂度,使增强层序列的解码PSNR平均提高了0.23 dB。     

基于帧拆分的MPEG视频的可靠传输

1.前言近年来在Internet上传送MPEG视频的需求和应用越来越多。多媒体交互式应用要求短时延,一般采用UDP协议进行传送,但UDP是不可靠传输协议,传送过程中的包丢失将导致视频质量下降。MPEG使用的帧间预测技术使得一旦I-帧或P-帧在传送中丢失,依赖它们的许多帧将受影响,即使很小的包丢失率也会严重影响接受到的MPEG视频的质量。     

一种针对整帧图像丢失的错误隐藏算法

在低码率的网络视频通信中,数据包丢失往往导致整帧图像数据的丢失。为了修复丢失的整帧图像数据,提出了一种基于光流场不变性的整帧图像错误隐藏算法。该算法首先使用有理插值对前帧图像的运动矢量场做预处理来得到稠密的运动矢量场;然后采用前向投影技术将前一帧图像内容沿着运动矢量场方向投影到当前图像的对应位置上。由于在图像运动场的突变而形成的重叠和遮挡区域,该算法对其按前景和背景进行区分处理,因而进一步提高了错误隐藏的性能。实验结果表明,和已有算法比较,用该算法修复的图像的峰值信噪比提高了0.18~0.82dB,同时得到了更好的主观图像质量。     

基于自适应遗传算法的SVC非均等错误保护算法

为提高可伸缩视频编码(SVC)在丢包的网络传输环境下的抗误码性能,提出了一种基于自适应遗传算法的SVC非均等错误保护算法。首先针对可伸缩视频编码的网络抽象层单元数据包头的特点,设计了一种新的网络抽象层单元的封装方案。然后将前向纠错编码的校验位在各层的分配转化为多约束条件下的优化问题,再引入惩罚函数将多约束优化问题转化为无约束优化问题,进而采用自适应遗传算法进行求解。仿真实验结果表明,与目前典型的非均等错误保护算法相比,该算法使重建的可伸缩视频编码的峰值信噪比的平均值提高了0.8 dB~1.95 dB,并有效提高了可伸缩视频编码在接收端的解码速度和重建质量。     

XOR-based frame loss recovery scheme for video streaming

High coding dependencies among video frames suffer from vulnerability to packet loss, which impacts the playback quality of video streaming. In this paper, according to the characteristics of MPEG4/H.264 encoding methods, we propose a simple and low-complexity XOR-based FEC frame loss recovery scheme. Within an entire Group of Pictures (GOP), the proposed scheme shows the ability to recover simultaneously I-frame loss and one P-frame loss. The high frame loss resilience improves the playback QoS of compressed video streaming. The mathematical analysis reveals that the proposed scheme has 72.7% performance improvement than no frame loss protection in term of full GOP frames successful decoding rate.     

基于TCP友好速率控制和前向纠错的MPEG-2视频传输

针对Internet视频传输面临拥塞控制和数据包丢失的问题，结合TCP友好的速率控制算法和前向纠错机制建立视频传输的分层体系构架和控制策略。传输体系同时采用以GOP为基本分析单元的视频帧速率预测模型，实现根据网络丢包率的变化动态地优化配置前向纠错的冗余信息。实验证明，传输体系采用动态优化的前向纠错能实时地适应带宽的变化，有效地降低数据包丢失带来的影响，从而改善视频回放质量。     

An unequal packet loss resilience scheme for video over the Internet

We present an unequal packet loss resilience scheme for robust transmission of video over the Internet. By jointly exploiting the unequal importance existing in different levels of syntax hierarchy in video coding schemes, GOP-level and Resynchronization-packet-level Integrated Protection (GRIP) is designed for joint unequal loss protection (ULP) in these two levels using forward error correction (FEC) across packets. Two algorithms are developed to achieve efficient FEC assignment for the proposed GRIP framework: a model-based FEC assignment algorithm and a heuristic FEC assignment algorithm. The model-based FEC assignment algorithm is to achieve optimal allocation of FEC codes based on a simple but effective performance metric, namely distortion-weighted expected length of error propagation, which is adopted to quantify the temporal propagation effect of packet loss on video quality degradation. The heuristic FEC assignment algorithm aims at providing a much simpler yet effective FEC assignment with little computational complexity. The proposed GRIP together with any of the two developed FEC assignment algorithms demonstrates strong robustness against burst packet losses with adaptation to different channel status.     

Robust transmission of scalable video stream using modified LT codes

LT codes are convenient and popular kind of rateless codes that could easily tolerate different patterns of loss in erasure channels. In this paper an LT code with unequal packet protection (UPP) property is proposed. The proposed code could provide unequal packet recovery to any importance-sorted data packets. Simulation results indicate the enhanced performance of the suggested scheme and its ability to increase the probability of early decoding of more important parts of data rather than the rest. Also it is shown that the proposed scheme could provide comparable bit error rates in comparison to the one of the well known previous methods. The code with modified encoding graph has been utilized for transmitting of the scalable data-partitioned video stream. Simulation results also illustrate the performance of the suggested approach in early delivery of the most important parts of a video sequence.     

A low complexity model for predicting slice loss distortion for prioritizing H.264/AVC video

The cumulative mean squared error (CMSE) is a widely used measure of distortion introduced by a slice loss. We propose a low-complexity and low-delay generalized linear model for predicting CMSE contributed by the loss of individual H.264/AVC encoded video slices. We train the model over a video database by using a combination of video factors that are extracted during the encoding of the current frame, without using any data from future frames in the group of pictures (GOP). We then analyze the accuracy of the CMSE prediction model using cross-validation and correlation coefficients. We prioritize the slices within a GOP based on their predicted CMSE values. The performance of our model is evaluated by applying unequal error protection, using rate compatible punctured convolutional codes, to the prioritized slices over noisy channels. We also demonstrate an application of our slice prioritization by implementing a slice discard scheme, where the slices are dropped from the router when the network experiences congestion. The simulation results show that (i) the slice CMSE prediction model performs well for varying GOP structures, GOP lengths, and encoding bit rates, and (ii) the peak signal-to-noise ratio and video quality metric performance of an unequal error protection algorithm using slices prioritized by the predicted CMSE is similar to that of the measured CMSE values for different videos and channel signal-to-noise. We also extend the GOP-level slice prioritization to frame-level slice prioritization and show its performance over noisy channels.     

Cross-Layer prioritized H.264 video packetization and error protection over noisy channels

Video transmission over wireless channels is affected by channel-induced packet losses. Distortion due to channel errors can be alleviated by applying forward error correction. Aggregating H.264/AVC slices to form video packets with sizes adapted to their importance can also improve transmission reliability. Larger packets are more likely to be in error but smaller packets require more overhead. We present a cross-layer dynamic programming (DP) approach to minimize the expected received video distortion by jointly addressing the priority-adaptive packet formation at the application layer and rate compatible punctured convolutional (RCPC) code rate allocation at the physical layer for prioritized slices of each group of pictures (GOP). Some low priority slices are also discarded to improve protection to more important slices and meet the channel bit-rate limitations. We propose two schemes. Our first scheme carries out joint optimization for all slices of a GOP at a time. The second scheme extends our cross-layer DP-based approach to slices of each frame by predicting the expected channel bit budget per frame for live streaming. The prediction uses a generalized linear model developed over the cumulative mean squared error per frame, channel SNR, and normalized compressed frame bit budget. The parameters are determined over a video dataset that spans high, medium and low motion complexity. The predicted frame bit budget is used to derive the packet sizes and corresponding RCPC code rates for live transmission using our DP-based approach. Simulation results show that both proposed schemes significantly improve the received video quality over contemporary error protection schemes.     

一种低延迟限制下H.264码率控制算法

对于实时、双向视频通信而言,减少传输时所造成的延迟是十分重要的。本文针对H.264视频压缩编码标准,提出了一种在低延迟条件下,仍可维持高画质并避免缓存区溢出的码率控制算法。鉴于I帧量化参数的选择对于整个GOP编码比特及失真的影响,本文通过对整个GOP的预测码率和失真做率失真优化,来选择可以平衡整个GOP编码量和失真的量化参数。同时增加一个主动跳帧策略,在缓存区未达饱和状态时,仍主动跳过一些并不重要的图像,而留出区空间使那些相对重要的图像可以保留。实验结果表明,在低延迟条件下,本文的方法不论在避免跳帧和维持画质方面均高于JVT新近采纳的JVT-H017提案。     

Generic forward error correction of short frames for IP streaming applications

If the frame size of a multimedia encoder is small, Internet Protocol (IP) streaming applications need to pack many encoded media frames in each Real-time Transport Protocol (RTP) packet to avoid unnecessary header overhead. The generic forward error correction (FEC) mechanisms proposed in the literature for RTP transmission do not perform optimally in terms of stability when the RTP payload consists of several individual data elements of equal priority. In this paper, we present a novel approach for generating FEC packets optimized for applications packing multiple individually decodable media frames in each RTP payload. In the proposed method, a set of frames and its corresponding FEC data are spread among multiple packets so that the experienced frame loss rate does not vary greatly under different packet loss patterns. We verify the performance improvement gained against traditional generic FEC by analyzing and comparing the variance of the residual frame loss rate in the proposed packetization scheme and in the baseline generic FEC.