A pretreatment to improve the quality metrics performance for encoding H264/AVC

The study of the human visual system is very interesting to quantify the quality of an image or to predict perceived information. The contrast sensitivity function is one of the main ways to incorporate the human visual system properties in an imaging system. It characterizes its sensitivity to spatial frequencies. In this paper, we are interested in establishing a pretreatment for existing metrics with full reference (“peak signal‐to‐noise ratio”, “digital video quality”) for the H.264/MPEG‐4 (Motion Picture Expert Group) advanced video coding standard. We realize in our algorithm the FFT transformation to apply the contrast sensitivity function. Our method is applicable to any size of image and video sequence by increasing its size at powers of two. This increase is achieved by adding “mirror image.” We evaluate the performance of the proposed pretreatment by using subjective “LIVE” video databases. The performance metrics, that is, Pearson (PLCC), Spearman correlation coefficients (SROCC) and root mean square prediction error (RMSE) indicate that the proposed method gives a good performance in H264 codec distortions.     

将MPEG2转换为MPEG4标准的视频编码器的实现

该文提出并实现了一个基于MPEG4的快速高效存储的视频编码器,用它把一个MPEG2视频数据流转换为一个低比特率、低空间分辨率的MPEG4流,并进行无线视频处理。与现有编码器相比,它不仅能够大大地节省实际需要存储空间,计算复杂度也降低了许多,实验结果表明该编码器得到的视频质量与像素领域方法得到的视频质量相当。     

Optimizing H.264/AVC interprediction on a GPU‐based framework

H.264/MPEG‐4 part 10 is the latest standard for video compression and promises a significant advance in terms of quality and distortion compared with the commercial standards currently most in use such as MPEG‐2 or MPEG‐4. To achieve this better performance, H.264 adopts a large number of new/improved compression techniques compared with previous standards, albeit at the expense of higher computational complexity. In addition, in recent years new hardware accelerators have emerged, such as graphics processing units (GPUs), which provide a new opportunity to reduce complexity for a large variety of algorithms. However, current GPUs suffer from higher power consumption requirements because of its design. Up to now, GPU‐based software developers have not taken this into account. In this paper, we present a detailed procedure to implement the H.264 motion estimation for a GPU, with the aim of reducing time and, as a consequence, the energy consumption. The results show a negligible drop in rate distortion with a time reduction of over 91.5% on average and it reduces the energy consumption by a factor of 11.78 compared with the reference implementation. Copyright © 2011 John Wiley & Sons, Ltd.     

H.264/AVC先进视频编码研究

为了取得更高的图像压缩性能和更多的实用功能，ISO／IEC MPEG(运动图像专家组)和ITU-TVCEG(视频编码专家组)共同制订了一套新的视频编码标准H．264／AVC。介绍了H．264／AVC图像编解码系统的实现过程，对其采用的新技术进行了描述，最后将其与H．263和MPEG-4标准进行了性能对比。     

基于MPEG4高效视频DCT编码器的实现

提出并实现了一个基于MPEG4的快速高效存储的DCT视频编码器，用它把H.261视频数据流转换为低比特率、低空间分辨率的MPEG4流，并进行无线视频处理。和现有编码器相比，它不仅能够大大地节省存储空间，计算复杂度也降低了许多，实验结果表明用该编码器得到的视频质量与用象素领域方法得到的视频质量相当。     

一种多功能图像编解码系统设计

JPEG2000算法在静止图像压缩中具有优良的性能,MPEG4和H.264算法则在运动图像压缩中具有优良的性能.但是在某些特殊情况下JPEG2000算法用在运动图像编码中也有一定的优势.介绍了一种通用的多功能图像编解码系统的设计,该系统既可用作编码板,又可用作解码板,而且兼容JPEG2000、MPEG4和H.264算法.另外,由于所有器件均为工业级,使得本系统用途非常广泛.     

一种MPEG1/MPEG2视频流的自适应播放算法

提出了一种MPEG1/MPEG2视频流的自适应播放算法。算法根据播放缓冲区的占用情况来调整视频帧的播放持续时间，并在播放缓冲区上溢时判断到达视频帧的类型，以决定是暂时存储还是丢弃，使得不会造成帧内编码帧和前向预测编码帧的丢失，从而保证视频流平滑地播放。实验结果表明，在播放不连续性和播放失真上新算法都优于Yuang算法，并实现了视频流的平滑播放。     

IEEE 802.11e中基于失真度度量的视频包传输方法

为改善H. 264编码的视频流在802. 11e中的传输性能, 提出了一种结合H. 264/AVC中不同类型的数据分割对视频重建质量的重要性因子和队列状态的视频包映射方法。首先定量分析H. 264/AVC中A、B、C三种分割的丢失对视频重建质量的影响, 得到其重要因子; 然后依据重要因子和队列长度将视频数据包映射到802. 11e的不同EDCA队列中。算法改进了EDCA机制中数据包的静态映射机制, 根据视频分割数据的不等重要性, 提供差异性服务。仿真结果表明, 与目前的视频包静态映射机制相比, 该算法提高了视频重建质量, 最好可提高1 dB以上。     

在MPEG视频上的语义视频对象分割改进算法

随着MPEG－4，MPEG－7等标准的提出，如何提取语义视频对象已成为当前视频压缩和检索领域共同的研究课题。特别是MPEG－7对视频对象的形状检索提出了具体要求。针对顾创等人的WaterShed算法不能很好处理现有MPEG－1视频数据的缺陷，提出改进算法，从而能够在MPEG视频流中提取到具有光滑轮廓的语义视频对象，算法主要有以下两点改进：提出将类成员数作为分类算法的参数；有压缩域和解码后的图像上先后进行两次分割。实验结果表明，改进算法在鲁棒性和分割结果精度上比原算法有较大的改进，其分割结果可用于轮廓检索和重要视频对象检索。     

一种适用于H．264的基于自适应搜索范围的快速运动估计算法

块匹配运动估计在视频编码中有着举足轻重的地位，其性能的优劣在很大程度上影响着输出码流的质量。全搜索是效果最好的运动估计算法，但其巨大的运算量是实际应用，特别是实时应用无法承受的。为解决这一问题，各种快速算法不断涌现。本文提出了一种适用于最新视频编码标准——H．264／MPEG4-AVC的快速运动估计算法。该算法基于自适应搜索范围，利用视频图像序列的帧间统计特性以及运动向量时域、空域的相关性，在保证PSNR性能的同时，使运动估计部分的运算复杂度大为降低。实验仿真表明，该算法适用面广，对大运动与小运动序列都有很强的自适应能力。在保持与全搜索相同PSNR的同时，平均速度超过全搜索280倍有余，超过三步法1．8倍，性能明显优于新三步法、四步法等经典快速运动估计算法。     

MPEG-2标准视频压缩分析

MPEG标准是数字音频和视频压缩的国际标准。MPEG-1是以低比特率步进扫描视频信号编码的标准。主要应用于交互式光盘(CD-1)。MPEG-2除了完全吸收了MPEG-1所采用的压缩编码技术,还采用了新增的算法工具以有效地对隔行扫描视频编码提供更高、更多的比特率,以支持广播质量业务和多信道环绕声编码。文中根据MPEG-2标准,介绍了其视频压缩的原理,给出一些视频编解码器的一般结构,并分析了其所用的两个关键技术。     

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.     

Enhancing aggregate QoS for video streaming

The IETF's Differentiated Services architecture is designed to provide different types or levels of service for Internet traffic. One of its key features is that traffic flows are aggregated so that routers in the core network only need to distinguish a relatively small number of aggregate flows, even if those flows consist of hundreds or thousands of individual flows. However, network-level QoS differentiation may not satisfy the requirements of many QoS-sensitive applications such as live video streaming, where end-to-end delay and reliability must be guaranteed.

This paper investigates application-level service differentiation for MPEG video streaming in a Diff-Serv-aware MPLS network infrastructure, along with routing support at the network layer. Based on the fact that MPEG video has become one of the most popular formats for Internet (wired and wireless) users, our approach enhances aggregate QoS for video streaming by employing existing application-level knowledge of the MPEG video structure; therefore it requires neither a new video compression algorithm nor additional bandwidth. Several MPEG video dispersion models are proposed and analyzed. Simulation results show that two such strategies are superior to the other tested. In addition, a new routing scheme is proposed to support searching the ‘best’ paths for efficient multi-path video streaming. Through extensive simulations, we demonstrate that our approaches improve the aggregate QoS of MPEG video streams, as well as overall network efficiency.     

Semi-blind quality estimation of compressed videos using digital watermarking

A semi-blind method that estimates the quality of a video distorted by H.264/AVC compression/decompression is introduced. The method embeds pseudo-random binary watermarks in the I-frames of the original undistorted video. To assess the quality of a segment of a distorted watermarked video, the watermark bits are extracted and the quality is estimated based on the similarity between the embedded and the extracted watermarks. To enable quality assessment for a large range of distortions, the derivative vectors of different scaled versions of each I-frame of the original video are obtained, using wavelet transform. The watermark bits that are embedded in the small wavelet scales are used to estimate the small distortions, while the bits embedded in the large wavelet scales are used to estimate large distortions. This is because the latter bits are more robust (to distortions) than those bits embedded in the small wavelet scales. The proposed method was tested on different video sequences which were distorted by compression/decompression using H.264/AVC with different quality factors. The simulation results show that the proposed method can accurately estimate the quality of a video and its frames in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) quality measures.     

基于小波变换的MPEG视频流预测模型

提出了一种基于小波变换的MPEG视频流的预测模型,该模型对原始数据做Haar小波变换以后,充分考虑尺度系数和乘子的不同统计特性,对尺度系数和乘子采用不同的预测模型分别预测,最终通过多重分形小波模型建模过程合成MPEG视频流序列。利用仿真和数学分析的方法对预测模型在刻画MPEG视频流的主要统计特性方面进行性能分析,从误差、数据的概率分布特性以及自相似特性等方面,证实了该预测模型的优越性能。     

一种基于MPEG4的运动估计模板选择算法

根据图像序列不同类型及运动矢量时间、空间分布特性,针对MPEG4图像压缩提出一种基于模板选择的运动估计快速算法,对剧烈运动,构建了一种非正则六边形搜索模板,对微小运动的图像应用小菱形模板.仿真结果表明,该算法与全搜索、三步搜索和菱形搜索相比,具有能在保证图像质量的前提下,减少运算量和复杂度的优点.     

数字音视频取证系统中的视频压缩技术简介

介绍了在远程视频网络传输中发挥着重要作用的高性能视频压缩技术,对主流的视频压缩标准M-JPEG、MPEG4和H.264进行了讨论。基于这三种标准编码方案,将高性能的视频编码应用到了所开发的网络式数字音视频取证系统中,取得了较好的效果。     

基于H.264/AVC的视频通信抗分组丢失方法研究

H．264／AVC是新的视频编码标准,其高效的编码效率和良好的网络适配性,使它在多媒体通信中得到广泛应用,然而由于Internet网络是一种不保证QOS的“尽力”网络,基于Internet网络的视频业务将不呵避免地受到数据分组丢失的影响,因此文中基于H．264编码算法的特点提出多种新颖的视频抗分组丢失方法,包括Tornado码的不等保护,利用SEI域自适应改变纠错能力和交互式防误码扩散等．综合使用该文提出的多种抗分组丢失方法,在高丢包率环境下,与使用简单误码掩盖算法相比,恢复图像的平均PSNR可以提高8～15dB,且算法与H．264标准兼容,没有过多增加信道负担和运算复杂度,具有实用价值．     

基于EM聚类的H.264压缩域视频对象实时分割算法

从压缩域直接分割视频对象比传统的像素域分割具有快速高效的特点,目前已有不少从MPEG域分割的方法,但从H.264压缩域分割的甚少。为此提出一种基于H.264域的实时分割运动对象方法,该算法先对当前视频帧进行全局运动估计和补偿,然后对4×4的运动矢量场进行分类处理,最后对非零运动矢量使用改进的EM聚类分割算法。本文算法对多个视频序列进行了实验,结果表明,该算法针对静止背景和运动背景的视频序列都能达到较精确的实时分割。     

基于总变分的MPEG解码算法

针对低比特MPEG图像序列出现的压缩痕迹,提出一种后处理正则化方法进行MPEG解码。首先由自适应量化得到一个原始视频DCT系数的量化区间,重建的视频序列投影到此区间内,其次视频是连续的静止图像,得到耦合时间维度和分离时间维度的两种总变分模型,最后利用经典的原-对偶算法求解提出来的凸优化模型,得到后处理MPEG解码视频序列。实验结果表明,总变分正则化函数能够一定程度上减轻压缩痕迹,提高解码视频的质量。