多视点视频编码的研究现状及其展望

阐述了多视点视频编码(MVC)的主要研究问题.其中首先介绍了MVC的体系结构和发展过程;然后详细讨论了MVC的研究内容,包括预测结构、提高MVC编码效率的技术和高层语法;最后在总结MVC研究现状的基础上,提出了MVC在3D视频应用中的研究思路.     

多视点编码中一种快速的模式选择方法

在多视点视频编码中,多尺寸的运动估计和视点估计被用来选择宏块的最优编码模式.这些技术大大提高了编码效率,但是却带来了庞大的计算复杂度,从而影响了多视点视频编码的广泛应用.提出了一种新的模式选择的快速算法,利用了相邻视点的模式相关性来减少执行不需要的模式.实验表明,所提出的快速模式选择算法在不降低编码效率的同时可以显著降...     

一种改进的多视点视频编码预测结构

多视点视频编码(Muti-view Video Coding,MVC)标准采用预测关系固定的编码结构,不能根据视频序列调整预测关系,导致无法获得更好的编码效率.本文针对这一缺陷提出一种确定预测结构的方法,首先对图像进行下采样获得粗粒度图像,然后利用粗粒度图像间的灰度方差获得灰度相近的视点,最后对所选取的灰度相近的视点运用全局视差确定I-视点.经实验验证,本文的方法可以提高编码效率并减少编码中的缓存容量.     

多视点编码中一种快速的模式选择方法

在多视点视频编码中,多尺寸的运动估计和视点估计被用来选择宏块的最优编码模式。这些技术大大提高了编码效率,但是却带来了庞大的计算复杂度,从而影响了多视点视频编码的广泛应用。提出了一种新的模式选择的快速算法,利用了相邻视点的模式相关性来减少执行不需要的模式。实验表明,所提出的快速模式选择算法在不降低编码效率的同时可以显著降低计算复杂度。     

多视点立体视频传输系统与错误隐藏算法设计

针对多视点立体视频数据量大、网络带宽受限等问题,提出了一种分组传输多路复用的多视点立体视频实时传输系统。系统将多视点数据通过H.264/AVC压缩编码后,在两个IP链路中进行分组复用,实现了立体视频在带宽受限网络中的实时传输;同时,为了解决IP网络传输中的丢包问题,提出一种联合时域视点间预测的错误隐藏算法。最后通过实验表明,本文错误隐藏算法可以提高多视点立体视频的解码质量。     

基于转移概率的多视点视频快速模式选择算法

针对多视点视频编码(MVC)中部分大宏块模式(SKI P/DIRECT模式,帧间16×16模式)相对于其它模式的计算复杂 度低,并且在编码所确定的最优模式中占有相当高比重的特点,本文提出一种基于转移概率 的多视点视频 快速模式选择算法。首先根据多视点视频当前编码宏块对应时间和视点间宏块及周围宏块的 位置几何关系, 建立宏块模式参考模型;其次比较参考模型中模式的时间相似度和视点间相似度;最后计算 模式之间的转 移概率,确定提前结束大宏块模式选择过程的阈值。实验结果表明,本文所提出的快速算法 平均节约MVC时间80.93%,编码质量平均下降0.04dB,码率平均增加0.27%。     

高效率的多视点视频编码预测结构*

预测结构是多视点视频编码(Multi-View Video Coding,MVC)研究的主要内容之一。MVC目前采用HHI(Heinrich-Hertz-Institute)提出的分层次B帧预测结构(HBP),比联播预测结构获得了更好的压缩效率。分析了多种预测结构,并针对平行摄像机采集的多视点视频序列,提出了一种新的预测结构AS_EIPP,该结构充分利用相邻视点间的相关性和多参考帧模式,进一步提高了压缩效率。在多视点视频软件测试平台JMVC8.3上进行验证,实验结果表明:新的预测结构在保证重建视频质量基本不变的前提下,压缩效率比HBP预测结构提高了1%～4%。     

分布式多视点视频编码中的立体边信息生成

新兴的分布式多视点视频编码通过在解码端使用立体边信息可充分挖掘传统单视点的时间相关性和多视点特有的视间相关性.研究了一种多视点运动预测的立体边信息生成算法,提出了近似视差估计和编码端掩模融合算法.实验证明,解码端采用近似的视差矢量,编码端传递某些先验信息,都能有效提高立体边信息精度,降低计算复杂度.     

IP网络信源信道联合编码策略

面向IP网络,讨论了一种信源编码的失真估计模型,并用典型的视频编码器作了验证.提出了一种基于包的信道编码方法,并将该方法引入信道编码的失真估计中,对一种信道编码的失真估计模型作了改进.以前述内容为基础,提出了两种信源信道联合编码策略,实验结果表明,这两种策略得到的最优结果在很大程度上提高了视频重建质量.     

多视点与深度视频编码技术研究综述

多视点与深度视频(MVD)可以有效表示自由视点视频,减少了需传输视点的个数,该表达形式正受到越来越多的关注,如何对MVD进行高效编码尤为重要.介绍了自由视点视频的发展现状及国内外研究概况,详细讨论了深度图像的高效编码技术及多视点与深度联合编码技术,并对多视点与深度视频编码技术进行了总结及展望.     

A joint encoder–decoder error control framework for stereoscopic video coding

Stereoscopic video coding (SSVC) plays an important role in various 3D video applications. In SSVC, robust stereoscopic video transmission over error-prone networks is still a challenge problem to be solved. In this paper, we propose a joint encoder–decoder error control framework for SSVC, where error-resilient source coding, transmission network conditions, and error concealment scheme are jointly considered to achieve better error robustness performance. The proposed joint encoder–decoder error control framework includes two parts: an error concealment algorithm at the decoder side and a rate–distortion optimized error resilience algorithm at the encoder side. For error concealment at the decoder side, an overlapped block motion and disparity compensation based error concealment scheme is proposed to adaptively utilize inter-view correlations and temporal correlations. For error resilience at the encoder side, first, the inter-view refreshment is proposed for SSVC to suppress error propagations. Then, an end-to-end distortion model for SSVC is derived, which jointly considers the transmission network conditions, inter-view refreshment, and error concealment tools at the decoder side. Finally, based on the derived end-to-end distortion model, the rate–distortion optimized error resilience algorithm is presented to adaptively select inter-view, inter- or intra-coding for SSVC. The experimental results show that the proposed joint encoder–decoder error control framework has superior error robustness performance for stereoscopic video transmission over error-prone networks.     

An integrated temporal error concealment for H.264/AVC based on spatial evaluation criteria

Owing to error-prone transmission networks, the compressed video bit stream is prone to packet loss in the transmission channel. This loss causes serious distortion and the distortion will propagate to successive frames, especially in highly compressed video coding standard. Therefore, it is very important to efficiently enhance the restored result. In this paper, an integrated temporal error concealment technique for H.264/AVC is proposed. The technique could effectively restore the corrupted data by adaptively integrating error concealment approaches with the adaptive weight-based switching algorithm. The integrated mechanism is based on spatial evaluation criteria, judged by boundary distortion estimation and texture intensity. Experimental results show that the technique could effectively enhance the performance of error concealment.     

Key-frame reference selection for non-feedback video communication

This article addresses the problem of reference picture optimization in video communication over error prone networks. A novel estimation model for transmission distortion is proposed. This model is capable of recursively estimating the overall end-to-end distortion caused by quantization, error propagation, and error concealment. Simulation results show that this model can accurately estimate channel distortion. Then, based on the distortion estimation model, a new non-feedback key-frame reference picture selection (KRPS) algorithm is developed. The optimum reference picture minimizes the transmission distortion under the rate-distortion optimization framework. Extensive experiment results demonstrate that the proposed KRPS algorithm substantially achieves more peak signal to noise ratio (PSNR) gain over traditional prediction, especially in low bit-rate transmission.     

视频图像中端至端失真估算的研究

视频图像数据量大、压缩码流抗误性低,而现有通信网络的承载能力有限、传输性能不可靠,往往造成解码重建视频图像质量致命性地降低。有效控制信源与信道编码,使端至端失真最小是提高解码重建视频图像质量的关键,而精确的失真估算模型是获得最小端至端失真的前提。对几种典型的端至端失真估算模型进行了简要分析,指出了这些模型中待解决的关键问题并展望了端至端失真估算模型良好的发展前景。     

Comparative Interactivity Analysis in Multiview Video Coding Schemes

In a multiview video system, interactivity is important for users and should be considered in the design of multiview video coding (MVC). In this paper, we present an interactivity evaluation model for MVC schemes by using both weighted random graph and Markov approaches. The main factors that affect both the interactivity and rate‐distortion (RD) performances of MVC schemes are analyzed and discussed in detail. By taking these factors into consideration, a new MVC scheme is proposed for high interactivity and RD gains. Experimental results show that the proposed scheme has a significant interactivity gain with little coding loss, compared to the state‐of‐the‐art benchmark. As an extension to RD performance analysis, the interactivity evaluation model can be used as a design tool of alternative schemes for a future interactive multiview video system.     

一种基于H．264的有效运动估计算法

运动估计算法是实时视频编解码技术的研究重点，高精度的匹配和补偿可以减少预测误差，提高视频图像的压缩效果．为降低在视频编码标准H．264中运动估计的高计算复杂度问题，提出了采用一种基于节点模型的可变形块匹配运动估计算法来搜索最佳运动矢量．该算法充分利用了H．264运动矢量的的统计特性和相关性，并采用基于像素差值分类的运动估计匹配准则．实验表明，在编码性能损失很小的条件下，该算法有效降低了视频压缩编码中运动估计的运算复杂度．     

Optimizing Motion Compensated Prediction for Error Resilient Video Coding

This paper is concerned with optimization of the motion compensated prediction framework to improve the error resilience of video coding for transmission over lossy networks. First, accurate end-to-end distortion estimation is employed to optimize both motion estimation and prediction within an overall rate-distortion framework. Low complexity practical variants are proposed: a method to approximate the optimal motion via simple distortion and source coding rate models, and a source-channel prediction method that uses the expected decoder reference frame for prediction. Second, reference frame generation is revisited as a problem of filter design to optimize the error resilience versus coding efficiency tradeoff. The special cases of leaky prediction and weighted prediction (i.e., finite impulse response filtering), are analyzed. A novel reference frame generation approach, called ?generalized source-channel prediction?, is proposed, which involves infinite impulse response filtering. Experimental results show significant performance gains and substantiate the effectiveness of the proposed encoder optimization approaches.     

Cross-layer optimized authentication and error control for wireless 3D medical video streaming over LTE

3D video for tele-medicine applications is gradually gaining momentum since the 3D technology can provide precise location information. However, the weak link for 3D video streaming is the necessary wireless link of the communication system. Neglecting the wireless impairments can severely degrade the performance of 3D video streaming that communicates complex critical medical data. In this paper, we propose systematic methodology for ensuring high performance of the 3D medical video streaming system. First, we present a recursive end-to-end distortion estimation approach for MVC (multiview video coding)-based 3D video streaming over error-prone networks by considering the 3D inter-view prediction. Then, based on the previous model, we develop a cross-layer optimization scheme that considers the LTE wireless physical layer (PHY). In this optimization, the authentication requirements of 3D medical video are also taken into account. The proposed cross-layer optimization approach jointly controls and manages the authentication, video coding quantization of 3D video, and the modulation and channel coding scheme (MCS) of the LTE wireless PHY to minimize the end-to-end video distortion. Experimental results show that the proposed approach can provide superior 3D medical video streaming performance in terms of peak signal-to-noise ratio (PSNR) when compared to state-of-the-art approaches that include joint source-channel optimized streaming with multi-path hash-chaining based-authentication, and also conventional video streaming with single path hash-chaining-based authentication.     

Selective Disparity Estimation and Variable Size Motion Estimation Based on Motion Homogeneity for Multi-View Coding

Multi-view video coding (MVC) is an ongoing standard in which variable size disparity estimation (DE) and motion estimation (ME) are both employed to select the best coding mode for each macroblock (MB). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs it from practical use. In this paper, a fast DE and ME algorithm based on motion homogeneity is proposed to reduce MVC computational complexity. The basic idea of the method is to utilize the spatial property of motion field in prediction where DE and variable size ME are needed, and only in these regions DE and variable size ME are enabled. The motion field is generated by the corresponding motion vectors (MVs) in spatial window. Simulation results show that the proposed algorithm can save 63% average computational complexity, with negligible loss of coding efficiency.