FGS视频流的码率分配算法研究

该文针对精细可分级编码(FGS)比特流在时变带宽网络上的传输,提出了一种基于视频序列率失真(R-D)特性的FGS增强层的码率分配算法,目标是减少接收端解码视频质量的波动,同时保持视频总体质量最优。首先建立一个在多帧图像增强层之间进行码率分配的最优化问题形式,并进行了合理的简化,然后利用线性内插原则建立描述各帧图像增强层率失真特性的R-D模型。由于各帧图像R-D曲线的单调特性,如此建立起来的最优化问题可以用简单的算法求出最优解。仿真结果表明,这个方案在保证解码视频质量恒定和保持视频总体质量最优两方面均收到了良好的效果,同时该方案的简易性使得它的实现和应用成为可能。     

一种基于视觉感知的H.264 码率控制算法

针对目前视频编码标准H.264 的码率控制算法未考虑人眼视觉感知、易导致编码 后视频图像质量波动的不足,提出了一种基于视觉感知的H.264 码率控制算法。首先,设计了 像素域的恰可察觉失真模型。在此基础上,根据各帧的恰可察觉失真的大小进行帧层比特分配。 其次,建立了基于结构相似度的率失真模型,并采用此模型设计了基本单元层(basic unit, BU) 的比特分配方案。最后结合二次速率-量化模型得到量化参数。实验结果表明,该算法与目前 H.264 中典型的码率控制算法相比,错误率降低了0.2%。     

基于视频通信的信道码码率分配方法

针对差错信道下视频信源的不等差错保护问题,设计一个新的信道码码率分配策略,对一个图片组中不同位置的帧给予不同强度的保护。该策略考虑了视频信源的误码扩散问题,分析了差错掩盖方法与信道失真计算的关系,通过在编码端有效估计信道差错所引入的失真并建立最优码率分配问题,利用遗传算法快速得到最优的信道码码率分配方案。实验采用H.264视频编码标准,结果证明该策略能较好地提升视频传输系统性能。     

基于相关性分析的MVC比特分配算法

针对目前尚未深入研究多视点视频编码（Multi—view Video Coding,MVC）码率控制的问题,提出了一种基于相关性分析的多视点视频编码码率控制算法。该算法的核心是先根据视差预测和运动预测的结构关系,将所有图像分成6种类型的编码帧,并改进二项式率失真模型,然后根据多视点视频相关性分析在各个视点之间进行合理的码率分配,将码率控制分成4层结构进行多视点视频编码的码率控制。其中,帧层码率控制考虑分层B帧等因素分配码率,基本单元层码率控制根据宏块的内容复杂度采用不同的量化参数。实验结果表明该码率控制算法实际码率与目标码率平均误差能控制0．6％。     

基于贪婪算法的MGS编码优化方法

提出一种基于贪婪算法的MGS可伸缩编码的码率控制优化方法。该方法以较低的计算复杂度优化MGS编码,根据不同帧类型和质量层类型的统计特性分别建立不同的率失真模型,并基于贪婪算法确定MGS的片层优化分配方案。实验结果表明,该方法在相同码率下明显提高解码图像的质量,平均峰值信噪比可提高0.5 dB。     

基于率失真优化的可伸缩视频编码码率分配

可伸缩视频编码的主要目标是生成空域、时域、质量可伸缩的视频流,其中如何进行有效的码率分配,以截取特定条件下最优的一段码流,对视频信号的网络传输十分重要。在研究现有JVTSVC中码率分配算法的基础上,提出了通过划分FGSNAL单元建立其近似的率失真特性曲线,从中选择构成凸壳的点作为率失真最优的候选截断点,并以此进行优化的码率分配的方法。在参考软件JSVM上的实现表明,对标准测试集中的序列截取相同需求条件下的码流时,相对于JVTSVC中现有率失真优化的码率分配方法,新方法的解码视频质量均有进一步的提高。     

一种HEVC低延时编码码率控制算法

传统码率控制方法常常引起视频编码器的率失真性能降底。为了在满足码率控制精度的同时改善编码器率失真性能,提出一种基于改进R-λ模型的帧级码率控制算法。根据帧率把待编码视频序列划分成多个控制单元,并为当前控制单元分配目标比特;根据控制单元层的可用比特数为当前GOP分配目标比特;根据GOP层的可用比特数为当前待编码帧分配目标比特,再利用改进的R-λ模型计算得到拉格朗日乘子λ进行编码。在通用测试条件下的实验结果显示,该算法具有较高的码率控制精度,同时改善了编码器的率失真性能。其平均码率相对误差为0.095%;以不开启码率控制的HM16.7作为基准,平均码率节省(BD-Rate)达到了2.6%。     

基于IP无线网络FGS视频传输的多乘积码方案

研究基于IP无线网络中精细粒度可伸缩性(FGS)视频的传输。基于包交换的IP无线网络通常由两段链路组成:有线链路和无线链路。为了处理这种混合网络中不同类型数据包的丢失情况,对FGS视频增强层数据运用了一个具有比特平面间不平等差错保护(BPUEP)的多乘积码前向纠错(MPFEC)方案进行信道编码。对FGS增强层每一个比特平面(BP),在传输层,采用里德—索罗蒙码(RS)提供比特平面间的保护;而在链路层,则运用循环冗余校验码(CRC)串联率兼容穿孔卷积码(RCPC)提供数据包内保护。还提出了一个率失真优化的信源—信道联合编码的码率配置方案,仿真结果显示出该方案在提高接收端视频质量方面的优势。     

面向H.264标准的改进码率控制方法

为降低H.264/AVC编码器码率控制的计算复杂度,提高码率估计的精确性和视频输出质量,提出了一种简单高效的率失真码率控制方法.基于残差信息服从拉普拉斯分布的假设,推导出精确的率失真模型.并利用线性模型和二次模型拟合率失真曲线,得到优化的R-1/Q和D-Q模型,极大地降低了算法的计算负担,而头信息预测模型的引入进一步提高总码率估计的精确性.自适应的分配各层目标码率,确定最优的量化参数.实验结果表明,与JVT-G012码率控制算法相比,该算法获得更高的编码效率,视频解码质量更加平稳,输出码率更精确.     

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。     

Constant quality rate allocation for FGS coding using composite R-D analysis

In this correspondence, we propose a constant quality rate allocation algorithm for fine granularity scalability (FGS) coded videos. The rate allocation problem is formulated as a constrained minimization of quality fluctuation. The minimization is solved using a composite rate distortion (R-D) analysis. For a set of video frames, a composite R-D curve is first computed and then used for computing the optimal rate allocation. This algorithm is efficient because it is neither iterative nor recursive. After the composite R-D curve is computed, it can be used for optimal rate allocation of any rate budget. Moreover, the composite R-D curve can be updated efficiently over sliding windows. Experimental results have shown both the effectiveness and the efficiency of the proposed algorithm.     

基于率失真特性的视频编码优化算法

率失真(R-D)优化是视频编码器中一项关键技术,然而当前广泛采用的独立率失真优化远未达到全局最优性能.为了进一步提升高效视频编码(HEVC)的压缩性能,提出了一种结合率失真依赖性和率失真特性的二次编码优化算法.首先,采用原始HEVC的方法对当前帧进行第一次编码,从而得到当前帧消耗的比特数和每个编码树(CTU)单元的率失...     

Linear Rate Control and Optimum Statistical Multiplexing for H.264 Video Broadcast

The H.264 video coding standard achieves significantly improved video compression efficiency and finds important applications in digital video broadcast. To enable H.264 video encoding for digital TV broadcast and maximize its broadcast efficiency, there are two important issues that need to be adequately addressed. First, we need to understand the complex coding mechanism of an H.264 video encoder and develop a model to analyze and control its rate-distortion (R-D) behavior in an accurate and robust manner. Second, the R-D behaviors of individual channels in the broadcast system should be jointly controlled and optimized under bandwidth and buffer constraints so as to maximize the overall broadcast quality. In this paper, we develop a linear rate model and a linear rate control scheme for H.264 video coding. We develop an optimum statistical multiplexing system to allocate bits across video programs (each being encoded by an H.264 encoder) and video frames so that the overall video broadcast quality is maximized. We study the bandwidth and buffer constraints in video broadcast and formulate the optimum statistical multiplexing into a constrained mathematical optimization problem. Realizing that it is impossible to find a close-form solution for global optima, we propose a simple yet efficient algorithm to find a near-optimum solution for joint rate allocation under buffer constraints. Our extensive simulation results demonstrate that the proposed statistical multiplexing system achieves about 40–50% saving in bandwidth, provides a smooth video quality change across programs and frames, and maintains robust decoder buffer control.      

FGS视频均等质量流化算法

细粒度扩展编码(FGS:Fine-Granularity-Scalability)由于具有很强的灵活性和较好的视频流化性能已经被MPEG-4和H.26L等标准所采用。论文在相关研究的基础上,采用了基于滑动窗口的算法来进行FGS视频的均等质量流化。该算法通过FGS的失真模型,使用二分法对当前窗口中的所有帧进行速率分配。实验表明,该算法可以较好地实现速率的优化分配,使连续图像质量的变化更加平滑。     

分布式视频编码中关键帧丢失错误保护

目的 分布式视频编码较其传统视频编码具有编码简单、误码鲁棒性高等特点,可以很好地满足如无人机航拍、无线监控等新型视频业务的需求。在分布式视频编码中,视频图像被交替分为关键帧和Wyner-Ziv帧,由于受到信道衰落和干扰等因素的影响,采用传统帧内编码方式的关键帧的误码鲁棒性远不如基于信道编码的Wyner-Ziv帧。关键帧能否正确传输和解码对于Wyner-Ziv帧能否正确解码起着决定性的作用,进而影响着整个系统的压缩效率和率失真性能。为此针对关键帧在异构网络中的鲁棒性传输问题,提出一种基于小波域的关键帧质量可分级保护传输方案。方法 在编码端对关键帧同时进行传统的帧内视频编码和基于小波域的Wyner-Ziv编码,解码端将经过错误隐藏后的误码关键帧作为基本层,Wyner-Ziv编码产生的校验信息码流作为增强层。为了提高系统的分层特性以便使系统的码率适应不同的网络条件,进一步将小波分解后图像的各个不同层的低频带和高频带组合成不同的增强层,根据不同信道环境,传输不同层的Wyner-Ziv校验数据。同时对误码情况下关键帧的虚拟噪声模型进行了改进,利用第1个增强层已解码重建的频带与其对应边信息来获得第2个和第3个增强层对应频带的更加符合实际的虚拟信道模型的估计。结果 针对不同的视频序列在关键帧误码率为1%20%时,相比较于传统的帧内错误隐藏算法,所提方案可以提高视频重建图像的主观质量和整体系统的率失真性能。例如在关键帧误码率为5%时,通过传输第1个增强层,不同的视频序列峰值信噪比（PSNR）提升可达25 dB左右;如果继续传输第2个增强层的校验信息,视频图像的PSNR也可以提升0.51.6 dB左右;如果3个增强层的校验信息都传输的话,基本上可以达到无误码情况下关键帧的PSNR。结论 本文所提方案可以很好地解决分布式视频编码系统中的关键帧在实际信道传输过程中可能出现的误码问题,同时采用的分层传输方案可以适应不同网络的信道情况。     

Joint Source-Channel Rate-Distortion Optimization for H.264 Video Coding Over Error-Prone Networks

For a typical video distribution system, the video contents are first compressed and then stored in the local storage or transmitted to the end users through networks. While the compressed videos are transmitted through error-prone networks, error robustness becomes an important issue. In the past years, a number of rate-distortion (R-D) optimized coding mode selection schemes have been proposed for error-resilient video coding, including a recursive optimal per-pixel estimate (ROPE) method. However, the ROPE-related approaches assume integer-pixel motion-compensated prediction rather than subpixel prediction, whose extension to H.264 is not straightforward. Alternatively, an error-robust R-D optimization (ER-RDO) method has been included in H.264 test model, in which the estimate of pixel distortion is derived by simulating decoding process multiple times in the encoder. Obviously, the computing complexity is very high. To address this problem, we propose a new end-to-end distortion model for R-D optimized coding mode selection, in which the overall distortion is taken as the sum of several separable distortion items. Thus, it can suppress the approximation errors caused by pixel averaging operations such as subpixel prediction. Based on the proposed end-to-end distortion model, a new Lagrange multiplier is derived for R-D optimized coding mode selection in packet-loss environment by taking into account of the network conditions. The rate control and complexity issues are also discussed in this paper     

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.     

Rate-Distortion Analysis and Quality Control in Scalable Internet Streaming

Rate-distortion (R-D) modeling of video coders has always been an important issue in video streaming; however, few of the traditional R-D models and their performance have been closely examined in the context of scalable (FGS-like) video. To overcome this shortcoming, the first half of the paper models rate-distortion of DCT-based fine-granular scalable coders and derives a simple operational R-D model for Internet streaming applications. Experimental results demonstrate that this R-D result, an extension of the classical R-D formula, is very accurate within the domain of scalable coding methods exemplified by MPEG-4 FGS and H.264 progressive FGS. In the second half of the paper, we examine congestion control and dynamic rate-scaling algorithms that achieve smooth visual quality during streaming using the proposed R-D model. In constant bitrate (CBR) channels, our R-D based quality-control algorithm dramatically reduces PSNR variation between adjacent frames (to less than 0.1 dB in sample sequences). Since the Internet is a changing environment shared by many sources, even R-D based quality control often cannot guarantee nonfluctuating PSNR in variable-bitrate (VBR) channels without the help from an appropriate congestion controller. Thus, we apply recent utility-based congestion control methods to our problem and show how a combination of this approach and our R-D model can benefit future streaming applications     

Bandwidth allocation for video transmission with differentiated quality of experience over wireless networks

Delivering digital video content with enhanced quality of experience to the end users over error-prone multi-hop wireless networks is a challenging issue. In video transmission over such wireless networks, many network-based (packet loss, delay, etc.) and source-based (encoding quantization level etc.) parameters can impose some levels of impairment on the perceived video quality. In a video quality enhancement strategy, accurate video quality metrics play a crucial role in the designing process of optimal rate (bandwidth) allocation algorithms. Many cross-layer optimization (CLO) based rate allocation strategies have been developed for this purpose which consider different objective functions (congestion level, total packet loss, etc.) in wireless networks. The main contributions of the proposed work are twofold. At first, an optimal bandwidth allocation framework is being developed in which based on some network-specific constraints and by incorporating an accurate video quality metric, the total weighted quality of experience of some competing video sources is being optimized bases on cross-layer design techniques. Secondly, these optimal rates have been used for differentiated Quality of Experience (QoE) enforcement between multiple competing video sources. The resulting optimal rates can be used as rate-feedbacks for on-line rate adaptation of a moderate video encoder such as MPEG4. The aforementioned weight parameters are selected based on the importance of each video sequence’s quality and can be associated with some previous service level agreement (SLA) based prices. Some numerical analysis have been presented to validate the theoretical results and to verify the claims.