视频通信中丢包损伤分析及客观测量方法

研究了多媒体通信中丢包对视频质量造成的影响以及相应的客观测量方法,在此基础上研究了各类丢包损伤的客观测量方法.实验结果表明,这些客观测量方法可以较为有效地表征视频通信中的丢包损伤.     

互联网视频业务图像质量的评估标准与方法

在基于互联网的视频应用中，图像质量直接反映了用户使用业务时的主观感受。本文介绍了图像质量的主观评价标准和客观测量方法，分析了互联网视频应用中信源端和用户接收端造成图像质量下降的原因，并对两种环境下图像质量的客观评估方法与指标做了探讨。     

H_265编码视频质量评价

本文着重研究了H．265编码的高清视频质量评价方法,以用于未来测试H．265编码器的性能。根据ITUVQEG的最新研究进展,介绍了高清视频的主观评价和客观测量方法,并且分析了目前已有的客观测量技术的主要实现方法和与主观评价方法相关度的结果,最后给出H．265编码视频质量测量技术的发展建议,并指出针对H．265编码器的测试,实验室环境,全参考的方法是首选,而无参考的方法是研究趋势。     

多媒体视频质量测量的研究和标准化

多媒体视频是电信运营商的重要业务,如何准确地测量多媒体视频质量,反馈给运营商,更好的监测管理,提升客户体验,至关重要.本文将从多媒体视频质量测量的应用需求、主观评价方法、客观测量方法、标准化等几个方面展开研究,重点分析视频视觉质量(PVQ)测量技术,其中无参考测量技术是目前国际研究和标准化的重点.在PVQ测量的基础上,...     

结合插帧技术的压缩视频质量增强算法

为了提升压缩视频的清晰度和帧率，提出了一种结合插帧技术的压缩视频质量增强算法。该算法主要包括帧率上变换部分和去压缩部分。在帧率上变换子网络，首先利用特征提取模块捕获相邻两帧的时空特征信息；其次使用插帧模块生成中间帧；最后将所有的视频帧和特征提取模块输出的特征信息一起输入去压缩子网络，进一步提高重建结果的质量。实验结果表明，该算法合成的视频帧更加自然真实，且能有效地去除压缩伪影，提升视频帧的主观与客观质量。     

一种基于视觉感知的视频质量客观评价方法

结合人眼视觉系统特性,讨论了视频的空域、时域信息以及由之产生的3个度量参数,提出了一种基于人眼视觉特性的客观视频质量的评价方法.实验结果表明,该方法能有效地反映人眼视觉机制,合理评价视频质量,在视频信号处理和图像压缩领域有着广泛应用前景.     

基于H.264码流的高清视频质量评价算法

提出了一种基于压缩域H.264视频流的高清视频质量客观评价方法.该算法直接从H.264视频码流中提取指定视频特征,通过线性拟合,建立各视频特征与最终图像质量之间的数学模型,从而实现对视频质量的客观评估.该算法定义了2个视频图像特征:度量压缩损伤的量化因子和编码跳过宏块数目.实验结果表明,基于这2个参数所获得的客观评价结果和主观感受具有较高的相关性.此外,由于该算法只需压缩码流中的特征参数即可实现可靠的快速评价,可广泛应用于实时终端场合.     

媒体资产管理系统中的视频图像质量评价研究

首先介绍了图像质量的主观评价和客观测量方法,具体分析了双刺激连续质量标度法和双刺激损伤标度法,根据媒资系统中各种视频图像的不同特点,针对性地提出了对应的图像质量评价方法,为当前电视台媒资系统性能的测试与评价提供参考。     

基于视频先验信息的轻量化去噪卷积神经网络

提出了一种基于视频先验信息的轻量化去噪卷积神经网络.先验信息从近邻的多帧视频图像中获取，采用了基于预去噪的视频运动补偿方法消除噪声和运动偏移对信息获取准确度的影响.为降低卷积神经网络复杂度，构建了基于双路处理的卷积神经网络用于去除视频噪声，特别是设计了双路稠密连接单元，实现了网络的轻量化.双路稠密连接单元通过高、低分辨率特征分解和特征拼接，有效降低了网络复杂度.实验结果表明：采用本文方法去除视频噪声能够获得较好的客观评价结果和主观视觉结果 .此外，在减少网络参数、降低浮点运算次数和提升运行速度方面均体现出了良好性能.     

MPEG-2全I帧压缩流的高清视频质量客观评价研究

主要研究对MPEG-2全I帧压缩的高清视频码流客观质量评价的方法,对不同码率的全I帧高清测试序列在压缩域进行压缩特征参数码率和平均量化因子的提取,并对其进行加权,得到客观质量评价值。实验结果表明,设计的视频质量客观评价系统得到的结果与主观评价具有较好的一致性,可用于MPEG-2全I帧压缩的高清视频质量评价。     

H.264结构相似性最优的宏块层码率控制算法

传统码率控制(RC)大多以客观失真作为失真度量,无法得到最优的主观质量。该文将基于结构相似(SSIM)的主观失真用于H.264视频编码的率失真优化和码率控制,提出了一种SSIM最优的宏块(MB)层码率控制(RC)算法。首先提出了一种经验型的SSIM线性失真模型,并结合改进的二次码率-量化(R-Q)模型用Lagrange乘子法得到了SSIM最优的MB层量化步长的闭式解。实验结果表明:该文算法相比客观质量最优的MB层RC算法JVT-O016更好地编码了图像结构信息,得到了更好的主观质量。     

几种主流视频编码方式的性能比较和分析

随着多媒体通信技术的不断发展,不同的组织提出了许多不同特点的编码方法。文中回顾并分析了当前一些主流的编码机制,通过峰值信噪比(PSNR)和最小察觉差(JND)对主流视频编码技术的质量性能进行了比较。通过比较发现,使用客观的PSNR标准时,H．264/AVC的各方面性能要好于现在使用的视频压缩标准,但选择主观的JND标准可能会略微影响不同编码的性能。     

Evaluation of objective quality metrics for multidimensional video scalability

Multidimensional video scalability refers to the possibility that a video sequence can be adapted according to given conditions of video consumption by adjusting one or more of its features such as frame size, frame rate, and spatial quality. An important issue in implementing an adaptive video distribution scheme using scalability is how to maximize the quality of experience for the delivered contents, which raises a more fundamental issue, that is, how to estimate perceived quality of scalable video contents. This paper evaluates existing state-of-the-art objective quality metrics, including both generic image/video metrics and ones particularly developed for scalable videos, on the problem of quality assessment of multidimensional video scalability. It is shown that, on the whole, some recently developed metrics targeting scalability perform best. The results are thoroughly discussed in relation to the nature of the problem in comparison to what has been reported in existing studies for other problems.     

VQeg validation and ITU standardization of objective perceptual video quality metrics

For industry, the need to access accurate and reliable objective video metrics has become more pressing with the advent of new video applications and services such as mobile broadcasting, Internet video, and Internet Protocol television (IPTV). Industry-class objective quality- measurement models have a wide range of uses, including equipment testing (e.g., codec evaluation), transmission- planning and network-dimensioning tasks, head-end quality assurance, in- service network monitoring, and client-based quality measurement. The Video Quality Experts Group (VQEG) is the primary forum for validation testing of objective perceptual quality models. The work of VQEG has resulted in International Telecommunication Union (ITU) standardization of objective quality models designed for standard- definition television and for multimedia applications. This article reviews VQEG's work, paying particular attention to the group's approach to validation testing.     

Hierarchical content importance-based video quality assessment for HEVC encoded videos transmitted over LTE networks

To improve the accuracy of assessment, many previous works take into account the video content. However, these previous works just only consider the video content, but do not consider the location and importance of the degraded content. Thus, this paper takes into account not only the video content, but also the location and importance of the degraded content, and proposes a hierarchical content importance-based video quality assessment. Firstly, we propose to use the hierarchical content importance-based frame degradation rate (HFDR) metric to quantify the importance of degraded content hierarchically. Secondly, we propose to use the intra random access point (IRAP) loss rate (ILR) metric to quantify the impact of IRAP. Finally, the proposed HFDR metric and ILR metric are subsequently used to develop an objective video quality assessment model. The experimental results show that the predicted mean opinion score (MOS) of the proposed method highly correlates with the actual MOS.     

A novel algorithm of Super-Resolution reconstruction for compressed video

Super-Resolution （SR） technique means to reconstruct High-Resolution （HR） images from a sequence of Low-Resolution （LR） observations, which has been a great focus for compressed video. Based on the theory of Projection Onto Convex Set （POCS）, this paper constructs Quantization Constraint Set （QCS） using the quantization information extracted from the video bit stream. By combining the statistical properties of image and the Human Visual System （HVS）, a novel Adaptive Quantization Constraint Set （AQCS） is proposed. Simulation results show that AQCS-based SR algorithm converges at a fast rate and obtains better performance in both objective and subjective quality which is applicable for compressed video.     

Q2ABR: QoE‐aware adaptive video bit rate solution

In this paper, we propose a new adaptive bit rate (ABR) streaming method. This method is based on estimating and monitoring users' video streaming experience, their quality of experience (QoE). This ensures a good user QoE and optimises bandwidth utilisation by monitoring video buffer fill rate to ensure minimal data traffic. First, we achieve a QoE evaluation model based on network bandwidth, video segment representation, and dropped video frame rate parameters. Second, following our QoE evaluation model, we formulate an ABR method using the reinforcement learning (RL) paradigm to select video representations and using a breakpoint detection mechanism to monitor end‐user QoE variation. The proposed ABR method is called “QoE‐aware adaptive bit rate (Q2ABR)” and is composed of three individual modules, one for QoE estimation using machine learning methods, one for QoE variation monitoring using the breakpoint detection mechanism, and one for video representation selection using reinforcement learning. The design objective of Q2ABR is to ensure the overall QoE of these users while maintaining a minimum variation in the standard deviation of the users' QoE values. Third, the performance of the Q2ABR method is evaluated and compared with several existing ABR approaches in the literature using real traces that we collect on different transport scenarios (such as bus and train, among others). Since this method considers the user's perception of video quality as a regulator for optimising the overall video distribution network, good results are ensured in terms of the user's experience and buffer fill rate.     

注意力模型指导下的视频质量评价方法

在视频质量评价方法中,常常需要对人眼视觉系统做出合理的假设,其中注意力模型就是一个很重要的因素。提出了一种在注意力模型指导下的视频质量评价方法,在图像帧的质量评价中加入了显著性区域信息,使之更能符合人眼视觉特性,并兼顾了视频中的运动信息,在一定程度上提高了客观质量评价方法的性能。     

基于多视点视频特征的3D-HEVC深度视频信息隐藏算法

为了更安全地传输秘密信息和保护3D视频,提 出基于多视点视频特征的3D-HEVC深度视频信息隐 藏算法。首先结合彩色视频的纹理特征,考虑深度视频不同区域对绘制视点的质量和编码效 率的影响,对 深度视频进行区域分割。然后针对不同的区域,采用不同的方式调制最大编码单元(LCU) 的QP值嵌入 秘密信息。最后,用修改后的QP值进行编码压缩,传输视频信息。实验仿真结果表明,相 比于原始HTM13.0, 本算法编码重建深度视频绘制视点质量的PSNR平均下降0.0015dB, 码率平均增加0.035%。本文算法 能较好地保证绘制视点的质量,对视频流的码率影响较小,且能实现秘密信息的盲提取。