A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

Rate Control Algorithm of Wireless Video Based on Visual Saliency Map Model

In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.

A Perceptual Video Coding Based on JND Model

In view of the fact that the current high efficiency video coding standard does not consider the characteristics of human vision, this paper proposes a perceptual video coding algorithm based on the just noticeable distortion model (JND). The adjusted JND model is combined into the transformation quantization process in high efficiency video coding (HEVC) to remove more visual redundancy and maintain compatibility. First of all, we design the JND model based on pixel domain and transform domain respectively, and the pixel domain model can give the JND threshold more intuitively on the pixel. The transform domain model introduces the contrast sensitive function into the model, making the threshold estimation more precise. Secondly, the proposed JND model is embedded in the HEVC video coding framework. For the transformation skip mode (TSM) in HEVC, we adopt the existing pixel domain called nonlinear additively model (NAMM). For the non-transformation skip mode (non-TSM) in HEVC, we use transform domain JND model to further reduce visual redundancy. The simulation results show that in the case of the same visual subjective quality, the algorithm can save more bitrates.

Frame-layer bit allocation for multi-view video coding based on frame complexity estimation

Current multi-view video coding （MVC） reference model in joint video team （JVT） does not provide efficient rate control schemes. This paper presents a rate control algorithm for MVC by improving the quadratic rate-distortion （R-D） model. We reasonably allocate bit-rate among views based on the correlation analysisl The proposed algorithm consists of three levels to control the rate bits more accurately, of which the frame layer allocates bits according to the frame complexity and the temporal activity. Extensive experiments show that the proposed algorithm can control the bit rate efficiently.

Variable Bit Rate Fuzzy Control for Low Delay Video Coding

Rate control plays a critical role in achieving perceivable video quality under a variable bit rate,limited buffer sizes and low delay applications.Since a rate control system exhibits non-linear and unpredictable characteristics,it is difficult to establish a very accurate rate-distortion(R-D)model and acquire effective rate control performance.Considering the excellent control ability and low computing complexity of the fuzzy logic in non-linear systems,this paper proposes a bitrate control algorithm based on a fuzzy controller,named the Fuzzy Rate Control Algorithm(FRCA),for All-Intra(AI)and low-delay(LD)video source coding.Contributions of the proposed FRCA mainly consist of four aspects.First,fuzzy logic is adopted to minimize the deviation between the actual and the target buffer size in the hypothetical reference decoder(HRD).Second,a fast lookup table is employed in fuzzy rate control,which reduces computing cost of the control process.Third,an input domain determination scheme is proposed to improve the precision of the fuzzy controller.Fourth,a novel scene change detection is introduced and integrated in the FRCA to adaptively adjust the Group-of-Pictures(GOP)length when the source content fluctuates.The FRCA can be transplanted and implemented in various industry coders.Extensive experiments show that the FRCA has accurate variable bit-rate control ability and maintains a steady buffer size during the encoding processes.Compared with the default configuration encoding under AI and LD,the proposed FRCA can achieve the target bit rates more accurately in various classical encoders.

Efficient Rate Control Algorithm for Hierarchical Video Coding

For rate control (RC) of hierarchical structure coding, an independent rate-quantization (R-Q) model was proposed based on mean absolute differences (MADs) in different temporal levels (TLs). In the proposed R-Q model, a novel MAD model was developed according to the hierarchical structure. The experimental results demonstrate that the proposed algorithm provides better performance, in terms of average peak signal-to-noise ratio (PSNR) and quality smoothness, than the H.264 reference model, JM14.2, under various sequences.

面向人体动作视频的语义编码传输方法

提出了一种高效的人体视频的无线传输方法,称为人体动作视频语义传输(AAST)系统。在当今的应用场景中,H.265视频编码和5GLDPC信道编码的组合已成为视频传输的常见方法。然而,在传输效率方面,尤其是在特殊情况下,仍存在相当大的提升潜力。受到最近人体动作视频研究的进展启发,提出了AAST系统。AAST系统能够以高效的方式传输关键区域的语义信息,并在接收端重建原始视频。鉴于关键区域运动语义信息内在的相关性,AAST系统采用非线性分析变换将运动信息映射到潜在空间。然后通过信源信道联合编码,将运动信息的潜在表示传输到接收端。在该系统中,利用潜在表示的先验信息来估计关键区域语义信息的重要性。这有助于在信源信道联合编码中实现自适应码率控制,从而带来显著的编码增益。大量的实验证明了AAST系统相对于其他有竞争性的视频传输系统具有更卓越的性能。值得注意的是,与H.265视频编码和5GLDPC信道编码传输方法相比,在达到相同的感知指标时,AAST系统最高可以节省约70%的信道带宽,展现了其在视频无线传输中的鲁棒性。

分布式视频编码中基于多概率混合分布的相关噪声建模方法

相关噪声建模(Correlation Noise Modeling,CNM)的准确度是影响分布式视频编码(Distributed Video Coding,DVC)系统性能的关键因素之一.针对经过8×8离散余弦变换(Discrete Cosine Transform,DCT)后的相关噪声子带,本文提出了全新的基于多概率混合分布的CNM方法.该方法可根据子带的信息熵与子带在柯西、拉普拉斯和高斯三种概率分布下信息熵的相似度,自适应选择合适的概率分布对子带进行建模,提高了CNM的准确度.实验结果表明,采用本文提出的离线和在线CNM方法与现有典型的CNM方法相比,DVC系统的率失真(Rate-Distortion,R-D)性能均获得显著的提高.

基于变换域Wyner-Ziv视频编码的相关噪声模型

在Wyner-Ziv(WZ)视频编码中,原始WZ帧数据和边信息(Side information,SI)间相关噪声模型是影响编码效率的关键因素。现有文献通常认为边信息和当前解码WZ帧的概率分布近似符合零均值拉普拉斯分布。本文详细研究了变换域WZ帧与相应边信息的残差系数的分布关系,发现其残差变换后直流系数带统计分布相比零均值拉普拉斯分布存在一定偏差,且系数带的相关噪声分布随时间和空间变换。根据变换域残差系数的分布特征,提出了一种基于变换域的相关噪声分布模型及自适应参数估计算法,利用帧内插时前向和后向运动补偿帧变换残差,在解码端估计系数带的分布参数。实验结果表明该算法有效提高了WZ视频编码的编码效率。

一种新的视频编码二次率失真模型及其性能分析

基于对视频编码比特率与内容复杂度之间关系的研究,该文提出了一种新的视频编码二次率失真模型。该模型保留泰勒级数中的常数项,并通过合理引入内容复杂度,提高了描述实际信源率失真特性的准确性。大量实验分析表明该模型具有良好的性能,可广泛应用于各种速率控制算法以及其他使用率失真模型的场合,以提高视频编码器的率失真性能。

MPEG-4编码的现状和研究

随着计算机和通信技术的发展，多媒体编码进入了一个新的时代，即将公布的ＭＰＥＧ－４国际标准表明基于对象的编码、基于模型的编码等第二代编码技术趋于成熟．文中首先从ＭＰＥＧ－４所支持的各种视频对象及其特点、场景的描述和不同应用的框架／级别等３个方面讨论了新的编码标准的主要内容和现状．新的标准用于实际应用还需要提供大量的标准之外的配套工具和研究．在随后的内容中，文中讨论了图像和视频的分割、全景图像的生成、人脸的检测与跟踪、２Ｄ网格模型的建立与跟踪以及３Ｄ人脸的分析和合成等相关领域的研究和进展情况．

一种改进的R-λ模型码率控制算法

码率控制是视频编码系统中的重要模块,用于控制编码器输出特定目标的码率,并使编码视频失真最小。R-λ模型码率控制方法是新一代视频编码标准HEVC中推荐的码率控制算法,其主要包括固定比例比特分配和自适应比率比特分配两种码率控制策略。为了提高R-λ模型码率控制算法的码率控制精度和率失真性能,文中提出了相应的算法改进。首先,根据图像组的编码结构设计了精确的率失真模型参数更新方法;其次,根据率失真依赖关系改进了图像组层的比特分配策略;最后,提出动态的图像组层拉格朗日乘子和编码帧比特权重计算方法。实验结果显示,所提方法在低延迟P帧和B帧配置下,码率相对误差仅为0.006%和0.005%,相比自适应比率比特分配码率控制策略,改进方法的率失真性能提高了1.2%和1.3%。

基于随机访问的多视点视频编码模式评价模型

运用随机图论、超空间等方法,首先提出了针对编码预测结构的随机访问性能评价函数,对解码端和服务器端的随机访问支持代价进行评价.进而根据实际应用中的带宽、交互限制等多种目标建立了编码策略评价的多目标非线性数学模型,对编码策略在多种性能参数约束条件下如何实现最优策略进行了讨论.利用该非线性多目标规划模型对多视点视频编码策略进行了优化设计,可以获得较好的随机访问性能.

无线移动环境视频编码动态功耗模型研究

移动终端在进行视频编码时往往受到功耗的制约。为了延长电池寿命周期,视频编码系统应能根据应用需求动态调节其编码复杂度。详细分析了典型视频编码系统各个主要模块及技术的复杂度,建立针对无线移动环境下的视频编码功耗模型。接着对该模型进行修正,并以量化参数和帧内刷新率作为参数,实现对功耗模型的动态调整。实验结果表明,该模型具有较高的精确性和鲁棒性,为实现可伸缩的功耗控制及优化提供理论指导。

脸部序列图像的模型基编码

本文以头部线框模型和图像处理、模式识别、计算机图形学技术为基础，提出了一套完整的会议电视头肩序列图像的分析—综合模型。在低于６４ｋｂｉｔ／ｓ的码率下，得到主观质量很高的图像。

采用改进高斯-牛顿法的视频弹性运动估计

运动估计是去除视频时间维冗余的编码技术，而目前通用的平移运动模型无法有效地表示物体的局部非刚性复杂运动．为此，提出一种基于改进高斯．牛顿法的弹性运动估计方法．首先，通过分析初始迭代点对高斯．牛顿迭代结果的影响，采用基于2bit深度像素的均匀搜索预测初始迭代点；其次，通过理论和实验分析发现，不同的迭代步长对弹性运动估计／补偿性能有明显的影响，采用离散余弦变换的低频能量比率估计步长的上限，再利用黄金分割法对步长进行求精．实验结果表明，对于具有不同场景特点的视频序列，该算法始终能够保持较高的估计精度，运动补偿的平均峰值信噪比，比基于块平移模型的全搜索算法和传统弹性运动估计算法分别提高1．73dB和1．42dB．并且，该算法具有更快的收敛速度，一般仅需1—3次迭代就能取得高于传统弹性运动估计和块平移全搜索的峰值信噪比．

移动环境视频编码功率-码率-失真模型研究

在前期建立视频编码动态功耗模型的基础上,将功率因子引入到经典率失真理论,并对经典码率模型及失真模型进行修正,进而建立视频编码功率-码率-失真模型.实验结果表明,该模型具有较高的精确性,为实现功耗约束条件下视频质量、带宽、功耗达到动态平衡的最优提供理论指导.

变换域Wyner-Ziv视频编码的码率控制

为了降低变换域Wyner-Ziv视频编码的解码复杂度,利用信道相关特征量及系数带的时间相关性提出了一种有效的码率控制算法.该算法在编码端估计传送的最小码率块,并利用不同系数带的时间相关性及信道的平均反馈次数,对估计的最小码率进行调整,得到实际需要传送的初始码率,从而有效地控制解码反馈次数,降低系统延时和解码复杂度.实验结果表明,该算法在保证编码效率的同时可以大幅降低解码复杂度,最大可降低82%.

分布式视频编码中虚拟信道模型的动态估计

针对分布式视频编码系统中虚拟信道的时域动态特性，提出了新的解码端帧级虚拟信道模型的动态估计算法。利用边信息内插阶段所获得的双向运动矢量，对当前帧前后的关键帧进行运动补偿，通过前后关键帧的运动补偿误差来估计当前帧的虚拟信道模型。针对虚拟信道的空域动态特性，还提出了子块级虚拟信道模型的动态估计算法。通过对视频帧进行分块，然后对每个分块都进行参数估计．即可动态地完成各子块对应的虚拟信道模型的估计。实验证明，对于不同运动特性的序列，所提出的虚拟信道模型可使系统的率失真性能提高0．5～1dB，有效地降低了视频编码系统的传输码率。

MPEG-4视频编解码器的模型分析、实现及其应用策略

在解读MPEG-4标准文档的基础上,较详尽分析了MPEG-4的DPCM/DCT视频编解码器混合模型及其设计与实现,并对MPEG-4各种应用提出了相应的策略。