视频转码中运动矢量自适应多模式精炼算法

针对视频转码中运动矢量重估计精度不高的问题,提出了一种运动矢量自适应多模式精炼(AMPR)算法.该算法首先利用输入码流中运动矢量的相位和幅值信息构建了视频局部区域活动性模型,通过此模型自适应确定精炼窗口的大小,然后在菱形搜索算法(DS)和水平垂直搜索算法(HAVS)的基础上,给出了多模式搜索策略.仿真实验表明,该算法取得接近于全搜索算法的视频质量,并有效地降低了计算复杂度.     

基于运动预测的Motion JPEG2000误码掩饰新算法

Motion JPEG2000(MJPEG2000)作为新兴的视频压缩标准,鲁棒传输控制是一个重要的应用需求,而误码掩饰技术是提高其鲁棒性的有效途径之一。充分利用压缩码流冗余信息,本文提出了一种基于运动预测的Motion JPEG2000视频传输误码掩饰新算法。首先利用相邻帧及帧内子带间的相关性进行小波域内的运动估计,以低频子带内码块的运动矢量来预测高频子带内丢失码块的运动矢量,再通过运动匹配修复丢失的码块。而低频子带内数据块的丢失可通过整个高频子带图像完成运动估计,得到预测信息对低频子带系数实施误码掩饰。仿真实验结果表明,提出的算法不管在低频还是高频子带进行误码掩饰修复,均能得到较好的图像帧重建效果。     

基于MPEG压缩域的运动对象检测方法

为了从MPEG压缩码流中准确的检测和提取运动对象,本文提出了一种时空域的运动对象检测算法。算法主要利用了MPEG码流中的运动矢量信息,首先对运动矢量进行时域平均和向量中值滤波的预处理,减少运动估计秒准确带来的运动矢量与实际对象运动带来的检测误差。然后建立时域上关于搜索块与参考块之间运动矢量夹角的概率模型,对于帧间预测宏块通过聂曼一皮尔迅准则进行运动判决。同时,对于P、B帧内的编码宏块,提出判决算法区分运动的帧内宏块和重现背景。实验证明,本文算法可以获得较为理想的检测效果。     

一种基于H.264的转码VoD系统实现

给出了一种基于H.264视频转码点播系统的实现,并在此基础上提出了在压缩视频空域下采样的快速模式选择算法.它通过利用原始输入码流中的运动向量及编码模式信息来获取下采样后的相应编码信息.试验结果表明:该算法在获得与级联解码器-下采样-编码器几乎一致的视频质量情况下,大大地降低了计算复杂度.     

基于背景前景分割的全局运动估计算法

文章提出一种直接对压缩视频码流进行全局运动估计的新算法。为了提高估计精度和计算效率．提出一种新的视频背景前景分割方法，该算法利用运动矢量和AC系数实现背景与前景分割。基于分割的结果，采用背景宏块的运动矢量进行全局运动参数估计。实验验证了提出的全局运动估计算法的计算效率和精度。     

基于GPU的视频转码技术研究

视频转码是个复杂的过程,它需要对已经压缩过的码流进行解析,然后经过处理转换成满足解码终端要求的目标格式码流。为了提高视频转码的效率并降低视频转码的计算复杂度,根据视频转码的要求和图形处理器的并行结构,提出了一种利用GPU强大的并行计算能力来加速视频转码的算法。该算法将视频转码过程中耗时最多、最复杂的运动估计和模式选择过程转移到GPU上并行执行。在开发GPU通用计算能力的时候,采用NVIDIA公司的CUDA(统一计算设备架构)计算平台。实验结果证明,该算法可以有效提高视频转码的速度和效率。     

一种新的基于H.264压缩域的运动对象分割算法

提出了一种在H.264压缩域下进行运动对象分割的新算法。算法主要利用H.264码流中的运动矢量信息来进行对象分割,为了提高运动矢量信息的鲁棒性,首先利用I帧中的帧内预测模式和预测残差能量进行区域划分;在P帧中,利用帧间预测残差能量来更新区域划分结果,对部分区域的运动矢量进行归零化处理。再根据P帧中的分块模式,采用不同的滤波器对运动矢量进行滤波;最后利用滤波后的运动矢量信息建立对应的Gibbs势能函数,采用迭代条件模式方法求解最大后验概率,得到可靠的运动对象标记。实验结果表明,该运动对象分割算法可以获得有效并可靠的分割结果。     

基于邻域运动一致性的运动矢量快速构建算法

在时移电视应用中,视频快进播放要求视频服务器能够通过跳帧抽取视频序列中的I帧和P帧的方式输出快速播放码流,当所跳帧中含有P帧时,必需对抽取出来的快进码流中的P帧进行重编码.为提高抽取后重编码效率,可利用码流中的原始运动矢量对跳帧后新参考帧条件下的运动矢量进行预测.在FDVS和ADVS算法基础上,提出了一种基于宏块及其相邻宏块运动一致性的算法来修正原始运动矢量,并通过实验将其与现有的FDVS和ADVS算法进行比较.     

基于CELP编码模型的参数转码技术

分析了基于CELP语音编码模型的参数转码算法,并以此为基础对关键性技术进行了总结,主要分析和描述了ISP系数、自适应码书、固定码书和码书增益参数的转码算法。设计并实现了一种G．729A8Kb／s到AMR—NB7．95Kb／s模式的参数转码算法,客观质量测试结果表明,该参数转码算法的合成语音质量略优于级联方法。     

基于H.264压缩域的运动目标检测算法

基于H264压缩域的运动目标检测算法。首先,从压缩码流中提取原始运动矢量场,采用中值滤波法滤除运动场中由噪声引起的运动矢量;再利用从压缩码流中提取的宏块分割类型初步排除一些分块较大的伪运动块;然后采用自适应阈值选取法定位出运动区域;最后,通过已定位的运动区域的特征进一步精确识别出运动目标。算法充分利用了H264码流中的运动矢量信息,简单易于实现,适用于智能监控,视频分析等领域。试验结果表明,该算法检测效果较好,且不需要对压缩码流进行全部解码。     

一种用于H.264视频容错转码的帧内宏块刷新算法

无线网络信道具有误码率高、延时抖动等不稳定的特性。为了保证视频信息从有线网络到无线网络中传输的质量,需要对视频进行容错转码。基于H.264容错转码系统,利用转码结构中解码部分的运动矢量信息,自适应地在编码部分进行帧内刷新,以提高视频的抗误码能力。实验结果对比表明,该帧内刷新算法能够以较少的比特率为代价,有效地提高了接收端的视频质量。     

Requantization transcoding for H.264/AVC video coding

In this paper, efficient solutions for requantization transcoding in H.264/AVC are presented. By requantizing residual coefficients in the bitstream, different error components can appear in the transcoded video stream. Firstly, a requantization error is present due to successive quantization in encoder and transcoder. In addition to the requantization error, the loss of information caused by coarser quantization will propagate due to dependencies in the bitstream. Because of the use of intra prediction and motion-compensated prediction in H.264/AVC, both spatial and temporal drift propagation arise in transcoded H.264/AVC video streams. The spatial drift in intra-predicted blocks results from mismatches in the surrounding prediction pixels as a consequence of requantization. In this paper, both spatial and temporal drift components are analyzed. As is shown, spatial drift has a determining impact on the visual quality of transcoded video streams in H.264/AVC. In particular, this type of drift results in serious distortion and disturbing artifacts in the transcoded video stream. In order to avoid the spatially propagating distortion, we introduce transcoding architectures based on spatial compensation techniques. By combining the individual temporal and spatial compensation approaches and applying different techniques based on the picture and/or macroblock type, overall architectures are obtained that provide a trade-off between computational complexity and rate-distortion performance. The complexity of the presented architectures is significantly reduced when compared to cascaded decoder–encoder solutions, which are typically used for H.264/AVC transcoding. The reduction in complexity is particularly large for the solution which uses spatial compensation only. When compared to traditional solutions without spatial compensation, both visual and objective quality results are highly improved.     

一种快速的DCT域MPEG-2到MPEG-1下采样转码技术

文章提出了一种快速的DCT域MPEG-2到MPEG-1准卷积下呆样算法。在转码过程中。头信忠保持不变，且要求将每四个相邻MPEG-2宏块变为一个下采样MPEG-1宏块：用最大最小距离方法确定下采样宏块的运动向量、用简单多数原则确定下采样宏块类型以及用加全平均方案确定下呆样宏块的量化参数。另外，对下采样视频转码失真来源进行了分析。实验结果表明我们提出的转码方案，在同样条件下与级联像素域转码器（TM5）相比，不仅其计算复杂性减少67．6％、PNSR提高0．1dB，而且具有很小的比特控制错误。     

Fast motion estimation and mode decision for H.264 reverse transcoding

A fast reverse motion estimation algorithm with smart mode decision for H.264 reverse transcoding is proposed. The best mode for the backward transcoded macroblock is obtained by analysing the motion vectors and modes decoded from the forward bitstream. A significant reduction in the transcoding complexity with negligible impact on rate-distortion performance has been achieved     

Detection of transcoded HEVC videos based on in-loop filtering and PU partitioning analyses

With the increasing maturity of video editing technology, forgers are more inclined to transcode videos to High Efficiency Video Coding (HEVC) videos, as HEVC not only enables people to enjoy high-definition videos but also allows broadcasters to stream it more efficiently across networks. Therefore, to verify the originality and authenticity, it is of great significance to propose an algorithm for detecting transcoded HEVC videos. In this paper, a theoretical model of video transcoding is first constructed, and a novel transcoding detection algorithm based on In-loop Filtering and Prediction Units (PU) Partition (IFPP) is proposed. By analyzing the statistical characteristics of strong and normal filtering modes in deblocking filtering and calculating offset values in Sample Adaptive Offset (SAO) filtering, the transcoding traces in inter-coded frames can be captured. In addition, PU partition statistics are also extracted to make full use of traces in intra-coded frames. By fusing these subfeatures, the proposed IFPP feature with 17 dimensions can be obtained, which is further fed to the Support Vector Machine (SVM) classifier. Finally, experiments are conducted on datasets with various coding parameters. Results show that the proposed algorithm outperforms existing algorithms and has better robustness.     

MPEG-2与MPEG-4间转码的关键技术研究与实现

视频转码技术的出现，解决了视频通信领域数据在不同系统和设备间互通互连的问题。本文主要研究了MPEG-2到MPEG-4的转换编码，提出了运动矢量映射的转码结构，并对其中的关键算法进行了研究和实现。仿真试验表明，本文结构和算法在保证了转换编码灵活性的同时，具有较好的转码效率和鲁棒性。     

DCT-based video downscaling transcoder using split and merge technique.

For a conventional downscaling video transcoder, a video server has firstly to decompress the video, perform downscaling operations in the pixel domain, and then recompress it. This is computationally intensive. However, it is difficult to perform video downscaling in the discrete cosine transform (DCT)- domain since the prediction errors of each frame are computed from its immediate past higher resolution frames. Recently, a fast algorithm for DCT domain image downsampling has been proposed to obtain the downsampled version of DCT coefficients with low computational complexity. However, there is a mismatch between the downsampled version of DCT coefficients and the resampled motion vectors. In other words, significant quality degradation is introduced when the derivation of the original motion vectors and the resampled motion vector is large. In this paper, we propose a new architecture to obtain resampled DCT coefficients in the DCT domain by using the split and merge technique. Using our proposed video transcoder architecture, a macroblock is splitted into two regions: dominant region and the boundary region. The dominant region of the macroblock can be transcoded in the DCT domain with low computational complexity and re-encoding error can be avoided. By transcoding the boundary region adaptively, low computational complexity can also be achieved. More importantly, the re-encoding error introduced in the boundary region can be controlled more dynamically. Experimental results show that our proposed video downscaling transcoder can lead to significant computational savings as well as videos with high quality as compared with the conventional approach. The proposed video transcoder is useful for video servers that provide quality service in real-time for heterogeneous clients.     

Motion estimation for video compression using Kalman filtering

Motion estimation plays an important role for the compression of video signals. This paper presents a new block-based motion estimation method using Kalman filtering. The new method utilizes the predicted motion and measured motion to obtain an optimal estimate of motion vector. The autoregressive models are employed to fit the motion correlation between neighboring blocks and then achieve predicted motion information. The measured motion information is obtained by the conventional block-based fast search schemes. Several algorithms based on either one- or two dimensional models using either nonadaptive or adaptive Kalman filters are developed. The analysis of computational complexity and the simulation results indicate that the proposed method achieves significant savings on computation along with smoother motion vector fields and similar picture quality, when compared to the conventional full search algorithm     

低复杂度的快速降尺寸视频转码算法

为了降低降尺寸视频转码的运算复杂度,提出一种基于支持向量机的快速转码模式决策算法。首先从输入的高分辨率视频码流中的编码信息里选取多维特征向量,并选择与模式特征匹配的核函数训练SVM分类器模型,建立高分辨率视频编码信息与降尺寸视频宏块编码模式之间的相关性;然后构建分层式SVM分类器对降尺寸视频中宏块模式进行阶梯式预测分类,以此缩减预测模式数量,提高转码效率。实验结果证明,算法可以节省高达67.31%的运算量,同时保证转码后视频的高质量。     

Robust mobile video streaming in a peer-to-peer system

In a peer-to-peer (P2P) video streaming system, peers not only consume video, but also route it to other peers in the system, where ordinary peers are assumed to have sufficient downlink speed and media capability. This assumption often fails when the P2P system consists of peers that are heterogeneous in their computing power, hardware, and media capability.In this paper, we address a problem of streaming video to mobile devices, which are less capable than ordinary peers. In order to stream video to mobile devices, transcoding is often required to render video suitable for their small display, limited downlink speed, and limited video decoding capability. However, performing transcoding at a single peer is vulnerable to peer churn, which leads to video disruption. We propose interleaved distributed transcoding (IDT), a robust video encoding scheme that allows peers more capable than mobile devices to perform transcoding in a collaborative fashion. IDT is designed in such a way that transcoded substreams are assembled into a single video stream, which can be decoded by any H.264/AVC baseline profile compliant decoder. Extensive simulations and its implementation in a real P2P system demonstrate that the proposed scheme not only reduces computational load at a peer, but also achieves robust streaming in the case of peer failure or packet loss due to adverse wireless channel conditions. We confirm this finding by analyzing the effect of distributed transcoding under peer failure.