一种通用的视频传输端到端失真度估算方法

在综合考虑差错扩散、差错掩盖策略及信道误码率的基础上,从像素级对端到端的视频传输差错扩散失真情况进行了分析,根据帧间相关系数和掩盖比率,提出了一种适用于各种时域差错掩盖方法的通用传输失真度估算模型.基于包丢失的仿真实验表明,该模型能够较好地近似估计出差错扩散失真情况,可以适应于各种不同的时域掩盖方法.实验还显示,基于该模型的宏块编码模式的帧内更新选择,与传统的R-D模式帧内更新算法相比,达到了较好地抑制差错扩散的效果,可适用于多种时域掩盖方法.     

一种适用于H.264的时域差错掩盖改进算法

视频压缩码流在信道传输时 ,由于受到信道带宽或者稳定性的影响 ,容易发生数据的损坏或者丢失 ,这样不仅会对当前的视频帧产生影响 ,而且差错会延续到随后的视频帧 ,因此 ,需要采用某种技术来降低差错的影响。针对这一问题 ,在对最新视频压缩标准 H.2 6 4研究的基础上 ,基于 H.2 6 4标准的框架 ,对已有的差错掩盖算法进行了改进 ,提出了适合 H.2 6 4编码标准的时域子块匹配差错掩盖算法。该算法首先采用 8× 8的子块代替 16× 16的宏块 ,作为差错掩盖的运算单元 ,然后对不同的子块采用不同的边界像素 ,利用边界匹配算法 ,并通过改进的 1/ 4像素精度菱形搜索法在参考帧内找到最佳匹配块。实验结果证明 ,由于该算法有效地利用了 H.2 6 4压缩码流里的信息 ,因此 ,同传统的时域差错掩盖算法相比 ,对差错信号有更好的恢复效果。     

立体视频传输中右通道整帧丢失的错误掩盖算法

当立体视频流通过网络传输时,由于网络拥塞等造成的数据包丢失常常会引起整个视频帧丢失.鉴于此,本文基于H.264/AVC视频编码标准提出了两种立体视频整帧错误掩盖方案,它们分别利用立体视频序列的不同特点来进行恢复.结果显示,利用这两种算法恢复的图像均能获得很好的主客观质量.     

Region-based error concealment of right-view frames for stereoscopic video transmission

Transmission of stereoscopic video stream through error-prone wireless channels results in the loss of blocks. In this paper, we propose a region-based error concealment method that exploits encoding modes, inter-view and intra-view correlations of stereoscopic video sequences. Based on the statistical analysis of the encoding modes of the surrounding macroblocks (MBs) and of the spatially corresponding MB in the neighboring frame, the lost MBs are classified into three types: (1) smooth MBs, (2) regular motion MBs and (3) irregular motion MBs. Following the classification, corresponding operations, including direct replacement, quarter-pixel motion and disparity compensation, and bilateral error concealment with adjustable weights, are applied to reconstruct the smooth MBs, regular motion MBs and irregular motion MBs, respectively. Experimental results show that the proposed method outperforms other existing error concealment methods for stereoscopic video transmission in terms of both objective and subjective evaluations.     

基于分层视差估计的立体图象编码

基于立体视频数据压缩的目的，提出了一种基于分层视差估计/补偿的立体图象编码方案。该方案是采用JPEG标准独立编码参数图象，并利用视差估计/补偿技术编码目标图象，应用分层马尔可夫随机场（MRF）模型。率失真（RD）模型以及交叠块匹配的混合视差估计/补偿算法，可得到光滑准确的视差场，与通常的变尺寸块匹配（VSBM）相比，该算法得到的视差补偿图象的峰值信噪比（PSNR）可提高2.5dB左右；双向半像素精度的视差估计/补偿的性能要比单向整像素搜索提高3dB，实验结果表明，该立体图象编码方案能有效地压缩立体图象数据，并可推广到立体序列图象的编码压缩中。     

一种基于平面运动视差不变性的立体视频整帧丢失重建技术

针对立体视频单个视点中的整帧丢失问题,提出基于平面运动视差不变性的差错隐藏方案。该方案主要包括两个部分:1)利用两个视点的运动一致性,根据视差定位目标位置,把正确接收视点的当前帧与前一帧的帧差投影到丢失帧所在视点,作为当前帧与前一帧的帧差,再由帧差及前一帧的像素值重建丢失的帧;2)根据空洞特征自适应地选择基于邻域的方法或基于运动向量的方法进行空洞填补。实验结果表明,所提算法能够高质量地重建丢失的帧,其重建质量优于现有算法。     

Recovering Connected Error Region Based on Adaptive Error Concealment Order Determination

Parts of compressed video streams may be lost or corrupted when being transmitted over bandwidth limited networks and wireless communication networks with error-prone channels. Error concealment (EC) techniques are often adopted at the decoder side to improve the quality of the reconstructed video. Under the conditions of a high rate of data packets that arrives at the decoder corrupted, it is likely that the incorrectly decoded macro-blocks (MBs) are concentrated in a connected region, where important spatial reference information is lost. The conventional EC methods usually carry out the block concealment following a lexicographic scan (from top to bottom and from left to right of the image), which would make the methods ineffective for the case that the corrupted blocks are grouped in a connected region. In this paper, a temporal error concealment method, adaptive error concealment order determination (AECOD), is proposed to recover connected corrupted regions. The processing order of an MB in a connected corrupted region is adaptively determined by analyzing the external boundary patterns of the MBs in its neighborhood. The performances, on several video sequences, of the proposed EC scheme have been compared with those obtained by using other error concealment methods reported in the literature. Experimental results show that the AECOD algorithm can improve the recovery performance with respect to the other considered EC methods.      

基于可变尺寸块运动矢量恢复的H.264时域差错掩盖算法

针对H.264帧间预测编码的新特点,提出了一种基于可变尺寸块运动矢量恢复的时域差错掩盖算法。该算法首先利用相邻宏块编码模式的相关性,根据周围宏块的编码模式判断受损宏块的编码模式及运动矢量恢复的宏块划分方式,分别对各个划分的子块进行运动矢量的恢复;然后利用相邻块运动矢量参考帧的相关性,根据相邻块运动矢量的参考帧确定匹配使用的参考帧;最后采用边缘失真匹配方法恢复运动矢量。实验结果表明,该算法同传统的差错掩盖算法相比,由于支持不同尺寸块运动矢量的恢复,因此,算法对差错信号能够获得更好的恢复效果。     

用于立体视频会议系统的立体对象分割与跟踪算法

基于对象的立体视频编码压缩技术能在立体视频会议系统中得到很好的应用，从立体视频信号中正确分割出立体视频对象是基于对象的立体视频编码压缩的一个前提条件，基于立体视频会议图像序列的时空特性和左右通道间的视差特性，提出了一种立体视频对象分割与跟踪算法，首先利用空域分割和运动检测相结合的方法，提取左通道中的运动物体；然后，提出一种左右通道间基于边缘轮廓的二级视差匹配算法，并根据已分割的左通道运动对象提取右通道的视频运动对象；最后利用对象边界轮廓的跟踪方法对后续图像中的运动对象进行快速跟踪，实验结果说明文中算法能够应用于立体视频会议图像序列的立体对象分割与跟踪。     

基于平面拟合恢复运动矢量的错误隐藏算法

针对压缩视频码流在无线信道传输过程中由于运动矢量失配导致重构图像质量的问题,提出了一种基于平面拟合恢复运动矢量的错误隐藏算法。首先,根据H.264视频标准具有多参考帧且相邻宏块间的相关性的特点,通过把与受损宏块直接相邻的每个分块的运动矢量定义为一个点,采用平面拟合方法表征小范围内相邻运动矢量的变化趋势,对受损宏块运动矢量进行重建,然后利用改进的边界匹配函数,选取最优运动矢量对受损图像进行恢复。实验结果表明,该算法不仅避免了AIC算法产生的块效应,而且在不同的RTP丢包概率下,该算法比AIC算法得到的峰值信噪比有0.3~2.5 dB的提升。     

高清立体视频的传输失真估计模型

针对高清立体视频序列分辨率大、宏块信息量少以及网络传输易出现差错的特点,提出一种能够估计高清立体视频端到端传输的失真模型。该模型能够考虑到丢包对后续帧的错误扩散以及立体视频左右视点帧之间的时空相关性,采用递归算法准确地估计失真,并运用时域帧拷贝的错误隐藏方法降低解码端的复杂度。仿真结果表明,失真模型的平均预测误差能控制在6%以内,对于不同特性和分辨率的立体视频序列,在不同网络环境下传输失真估计均有一定的适用性。     

基于纹理检测的视频序列误差掩盖

文章提出了一种新的误差掩盖(ErrorConcealment)算法,作为在解码器端的后处理工具去解决视频序列在传输过程中产生的块及其运动矢量同时丢失的问题。笔者利用LOG算子去对丢失块周围的块进行纹理检测,取所有属于纹理块的运动矢量的平均值,作为丢失运动矢量的估计。仿真结果表明对不同块丢失率或不同视频序列,此算法都能比传统的方法恢复出质量更高的图像。     

Video Error Concealment Using Spatio-Temporal Boundary Matching and Partial Differential Equation

Error concealment techniques are very important for video communication since compressed video sequences may be corrupted or lost when transmitted over error-prone networks. In this paper, we propose a novel two-stage error concealment scheme for erroneously received video sequences. In the first stage, we propose a novel spatio-temporal boundary matching algorithm (STBMA) to reconstruct the lost motion vectors (MV). A well defined cost function is introduced which exploits both spatial and temporal smoothness properties of video signals. By minimizing the cost function, the MV of each lost macroblock (MB) is recovered and the corresponding reference MB in the reference frame is obtained using this MV. In the second stage, instead of directly copying the reference MB as the final recovered pixel values, we use a novel partial differential equation (PDE) based algorithm to refine the reconstruction. We minimize, in a weighted manner, the difference between the gradient field of the reconstructed MB in current frame and that of the reference MB in the reference frame under given boundary condition. A weighting factor is used to control the regulation level according to the local blockiness degree. With this algorithm, the annoying blocking artifacts are effectively reduced while the structures of the reference MB are well preserved. Compared with the error concealment feature implemented in the H.264 reference software, our algorithm is able to achieve significantly higher PSNR as well as better visual quality.     

用于IP网络的差错复原编解码器

随着因特网的飞速发展,基于IP网络的视频通信越来受到重视,但由于IP网络属于易于发生差错的信道,因此,基于IP网络的视频业务必须要到信道差错的影响,为了抗信道差错,差错复原技术已成为易发生差错信道下视频编码的重视组成部分,针对IP网络时常发生拥塞和带宽经常变动而造成的数据分组丢失,时延和抖动问题,提出了用于IP网络的差错复原技术综合应用解决方案,该方案通过综合运用多种差错原复技术,大大提高了压缩码流的抗差错能力和解码器和差错复原能力,同时应用该方案实现了具有差错复原性能的H．263、H．26L视频编码解器。利用Internet网络模型对编解码器的差错复原能力进行了实验,实验结果表明,该视频编解码器具有良好的差错复原性能,重图象的主客观质量得到了明显的改善。     

Decision trees for error concealment in video decoding

When macro-blocks are lost in a video decoder such as MPEG-2, the decoder can try to conceal the error by estimating or interpolating the missing area. Many different methods for this type of post-processing concealment have been proposed, operating in the spatial, frequency, or temporal domains, or some hybrid combination of them. In this paper, we show how the use of a decision tree that can adaptively choose among several different error concealment methods can outperform each single method. We also propose two promising new methods for temporal error concealment.     

Concealment of Whole-Picture Loss in Hierarchical B-Picture Scalable Video Coding

H.264/AVC scalable video coding (H.264/AVC SVC), as the scalable extension of H.264/AVC, offers the flexible adaptivity in terms of spatial, temporal and SNR scalabilities for the generated bitstream. However, such compressed video still suffers from the bad playback quality when packet loss occurs over unreliable networks. In this paper, we present an error concealment algorithm to tackle the whole-picture loss problem in H.264/AVC SVC when hierarchical B-picture coding is used to support temporal scalability. In the proposed algorithm, by taking advantage of the temporal relationship among the adjacent video pictures, the motion information of the lost picture is derived simply and efficiently based on the principle of temporal direct mode. Utilizing the derived motion information, the lost picture is concealed by performing motion compensation on the correctly received temporally previous and future video pictures. The experimental results demonstrate that as a post-processing tool, the proposed error concealment algorithm is able to significantly improve both the objective and subjective qualities of the decoded video pictures in the presence of packet losses when compared to the error concealment algorithm used in H.264/AVC SVC reference software. The proposed method can also be applied to H.264/AVC with hierarchical B-picture coding for error concealment.     

时空域相结合的视频差错掩盖方法

为了克服视频解码端时域差错掩盖技术不能准确估计丢失块运动矢量的缺点,提出了一种将解码端运动估计和隐藏运动模型相结合的误码差错掩盖方法。首先,利用丢失块 周围正确接收像素估计丢失块运动矢量,并计算估计的准确性。然后根据准确性,通过隐藏运动模型充分利用丢失块的空域和时域相关性进行差错块的掩盖。仿真结果表明,与现 有的算法相比,该方法能有效提高重建视频图像质量平均近1dB。     

基于H．264的立体视频右图像整帧丢失错误隐藏算法

当H．264编码立体视频流在Internet上传输时，由于信道错误所引起的数据丢失常常会造成整帧图像的丢失。为了恢复丢失的整帧立体视频右图像，提出了一种基于H．264的立体视频右图像整帧丢失错误隐藏算法，该算法依据立体视频编码特点进行相关性分析，首先确定丢失帧中每个宏块的预测方式，然后采用运动补偿或视差补偿对其进行恢复，进而重现丢失帧。实验结果表明，该算法能够在较低的计算复杂度下，获得较高质量的立体视频图像。     

高效率视频编码中基于块整合的错误隐藏算法

针对新一代视频编码标准高效率视频编码(HEVC)编码单元(CU)尺寸较大所导致的丢包后错误隐藏恢复效果不佳的问题,提出了对CU下的分割块进行块融合的错误隐藏方法。首先,分析了残差能量与块分割的相关性;然后,通过参考帧残差能量与所设阈值进行比较判决,对当前丢失CU分割块进行融合,得到丢失CU的块分割方式;其次,对矢量外推法进行权值优化,保证了算法在HEVC错误隐藏的适用性;最后,对融合块采用优化后的矢量外推法进行错误隐藏。实验结果表明,与经典错误隐藏方法如拷贝法、运动补偿法等相比,基于块融合的错误隐藏在保证解码视频结构相似性(SSIM)的同时提高了不同运动性的解码视频峰值信噪比(PSNR),验证了算法的可行性。