基于无线H．264时域误码掩盖算法的改进

为解决传统H.264时域误码掩盖算法中丢失块的相邻运动矢量在无线环境下极易丢失的问题,结合部分误码掩盖算法研究成果,提出了一种利用相邻参考帧和丢失块相邻运动矢量,运用投影加权的方法估计出最优丢失块运动矢量用于误码补偿的改进误码掩盖算法.实验证明,运用改进算法掩盖后的图像质量有所提高,并且抑制了误码的错误积累和扩散,具有一定实际应用意义.     

基于多方向边界匹配的视频误码掩盖算法

视频压缩码流对于信道误码十分敏感,可能导致重建图像质量严重下降.误码掩盖技术利用图像在时间和空间上的相关性,可以有效地降低误码对视频图像的影响.文中提出了一种基于多方向边界匹配的时域误码掩盖算法.该算法能更精确地恢复错误宏块的运动矢量,从而获得比传统的时域掩盖算法更好的视频质量.     

基于人脸特征的自适应空域差错掩盖算法

针对在视频通信中,高压缩视频码流对通信信道中由于信道带宽、环境等影响出现的丢包和误码极为敏感,本文提出一种在解码端基于人脸检测的自适应空域差错掩盖算法,根据正确接收帧的人脸位置及人脸运动的趋势预测受损帧人脸的位置,对于受损帧人脸内五官区域的宏块采用水平双线性插值,对于背景区域宏块采用自适应多方向插值算法。实验结果表明与现有算法相比主客观质量都有所提高。     

基于无线网络的H.264误码掩盖算法的改进

视频压缩码流在无线网络传输过程中受无线网络环境的影响丢包现象严重,重构图像质量下降.在H.264时域误码掩盖算法的基础上,根据时域和空域相邻宏块的运动矢量对丢失宏块的分割模式进行自适应选择,采用改进的边界匹配误差函数,估计丢失宏块的运动矢量.在无线网络环境下对多种视频序列和宏块丢失率进行仿真,图像质量有一定的提高.在宏块丢失率为10%情况下,峰值信噪比相对H.264标准算法提高0.08～1.13 dB.     

基于H.264的改进时域误码掩盖算法

提出一种模式自适应的误码掩盖算法。对宏块进行误码掩盖时,对宏块的模式进行估计,选择最优的模式进行误码掩盖。这样可以近似地恢复了宏块运动矢量和编码模式,而不是通常算法中仅仅只恢复运动矢量。通过一定的实验测试,该算法在不同的序列和不同的丢包率均稳定的优于单一模式的误码掩盖算法。     

基于MV自适应选取的帧间隐藏算法

数字视频通信在多媒体通信系统中占据重要的地位,但视频帧传输错误将导致接收视频质量的下降.视频帧传输错误不仅会破坏当前的解码帧,还会在时间上扩散造成对后续帧的预测错误.为减少视频帧传输错误对视频质量的影响,设计了一种基于运动矢量自适应选取的错误隐藏算法,算法充分利用相邻宏块间运动矢量的空间相关性来自适应地恢复受损宏块的运动矢量.仿真实验结果表明,相对于典型的错误隐藏算法,所述算法在主观视觉质量和客观评价指标上都有一定的提高.     

基于H.264/AVC的多参考帧时域误码掩盖

根据H．264／AVC编码的新特点,提出两种基于多参考帧的误码掩盖方法：一种是基于运动矢量均值的多参考帧误码掩盖;另一种是基于加权的多参考块的误码掩盖。仿真实验表明,解码后的图像质量优于H．264／AVC传统校验模型JM5．0的误码掩盖方法。     

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。     

面向三维高效视频编码的深度图错误隐藏

基于多视点视频序列视点内、视点间存在的相关性,并结合视点间运动矢量共享技术,该文提出一种面向3维高效视频编码中深度序列传输丢包的错误隐藏算法。首先,根据3D高效视频编码(3D-HEVC)的分层B帧预测(HBP)结构和深度图纹理特征,将深度图丢失块分成运动块和静止块;然后,对于受损运动块,使用结合纹理结构的外边界匹配准则来选择相对最优的运动/视差矢量进行基于位移矢量补偿的错误掩盖,而对受损静止块采用参考帧直接拷贝进行快速错误隐藏;最后,使用参考帧拆分重组来获取新的运动/视差补偿块对修复质量较差的重建块进行质量提升。实验结果表明:相较于近年提出的对比算法,该文算法隐藏后的深度帧平均峰值信噪比(PSNR)能提升0.25～2.03 dB,结构相似度测量值(SSIM)能提升0.001～0.006,且修复区域的主观视觉质量与原始深度图更接近。     

一种基于贝叶斯决策的自适应运动估计算法

为了提高视频编码运动估计中运动矢量预测的速度和准确性,提出一种基于贝叶斯决策的视频自适应运动估计算法.该算法充分利用贝叶斯理论、运动矢量的空间一致性和己编码帧对当前帧的影响,根据视频中前一帧和当前帧的已搜索宏块的运动信息,以目标宏块周围3个宏块的运动矢量与目标宏块的运动矢量空间距离最小为原则,利用贝叶斯决策来得到目标宏块运动矢量的预测值.实验表明,该方法在图像重建质量基本不变的情况下,比DS,ARPS和ARPS-3具有更快的搜索速度.     

Fuzzy Logic Based Temporal Error Concealment for H.264 Video

In this paper, a new error concealment algorithm is proposed for the H.264 standard. The algorithm consists of two processes. The first process uses a fuzzy logic method to select the size type of lost blocks. The motion vector of a lost block is calculated from the current frame, if the motion vectors of the neighboring blocks surrounding the lost block are discontinuous. Otherwise, the size type of the lost block can be determined from the preceding frame. The second process is an error concealment algorithm via a proposed adapted multiple‐reference‐frames selection for finding the lost motion vector. The adapted multiple‐reference‐frames selection is based on the motion estimation analysis of H.264 coding so that the number of searched frames can be reduced. Therefore the most accurate mode of the lost block can be determined with much less computation time in the selection of the lost motion vector. Experimental results show that the proposed algorithm achieves from 0.5 to 4.52 dB improvement when compared to the method in VM 9.0.     

基于可变块运动矢量的边信息生成算法*

在分布式视频编码系统中,针对图像中细节丰富的区域易造成严重的块效应,提出了一种基于可变块运动矢量的边信息生成算法。根据前后相邻关键帧对应块的相关性,将像素块分为保留块和运动块。对保留块直接作保留处理,对运动块中的像素块继续进行分割并计算子块的初始运动矢量,最后将所有对应块的运动矢量进行加权自适应运动补偿得到改进的边信息。实验结果表明,对于运动较剧烈复杂的视频序列,该算法能够提高边信息生成质量, 并且使得改进后的边信息PSNR值提高了0.98~1.33 dB。     

Frame Error Concealment Using Pixel Correlation in Overlapped Motion Compensation Regions

In low bit‐rate video transmission, the payload of a single packet can often contain a whole coded frame due to the high compression ratio in both spatial and temporal domains of most modern video coders. Thus, the loss of a single packet not only causes the loss of a whole frame, but also produces error propagation into subsequent frames. In this paper, we propose a novel whole frame error concealment algorithm which reconstructs the first of the subsequent frames instead of the current lost frame to suppress the effects of error propagation. In the proposed algorithm, we impose a constraint which uses side match distortion (SMD) and overlapped region difference (ORD) to estimate motion vectors between the target reconstructed frame and its reference frame. SMD measures the spatial smoothness connection between a block and its neighboring blocks. ORD is defined as the difference between the correlated pixels which are predicted from one reference pixel. Experimental results show that the proposed algorithm effectively suppresses error propagation and significantly outperforms other conventional techniques in terms of both peak signal‐to‐noise ratio performance and subjective visual quality.     

一种基于双域拉格朗日插值的视频错误隐藏方法

本文提出了一种基于双域拉格朗日插值的错误隐藏方法,编码采用H.264标准,分别在时域和空域进行插值获得两个运动矢量,通过建立插值系数表构造混合的插值模型,经过边缘匹配算法判断后获得最优的运动矢量作为丢失宏块的运动矢量.为了减小网络突发错误对插值效果的影响,本文在编码端提出了一种类交织的slice划分方法,实验证明本文方法由于充分利用了时域和空域的信息冗余,取得了较好效果,在15％网络丢包率的环境下平均PSNR比空域拉格朗日插值方法高0.5dB~1dB左右.     

A motion vector recovery algorithm for digital video using Lagrange interpolation

In this paper, we propose an efficient motion vector recovery algorithm for the new coding standard H.264, which makes use of the Lagrange interpolation formula. In H.264, a 16/spl times/16 inter macroblock can be divided into different block shapes for motion estimation, and each block has its own motion vector. For nature video the movement within a small area is likely to move in the same direction, hence the neighboring motion vectors are correlative. Because the motion vector in H.264 covers smaller area than previous coding standards, the correlation between neighboring motion vectors increases. We can use the Lagrange interpolation formula to constitute a polynomial that describes the motion tendency of motion vectors, which are next to the lost motion vector, and use this polynomial to recover the lost motion vector. The simulation result shows that our algorithm can efficiently improve the visual quality of corrupted video.     

Efficient error localization and temporal concealment based on motion estimation of enlarged block

We propose a modified motion estimation algorithm that is adequate for error localization and temporal error concealment in transmitting videos over unreliable channels. In order to achieve good error concealment performance, the proposed algorithm implicitly imposes spatial correlations on motion vectors by extending the block size and overlapping blocks in motion estimation. Thereby, the obtained motion vectors can be used to improve error concealment performance while keeping the encoding efficiency with negligible overhead. In addition, the proposed motion estimation can provide a new error detection measure so that we can maximally utilize uncorrupted data rather than simply discarding all data in a defected packet. Simulation results show that the proposed motion estimation scheme provides significant improvements in error concealment performance over the existing schemes and improves the bit utility over a wide range of error conditions.     

A Modified Block Matching Motion Estimation Algorithm for the Very Low Bit-Rate video Coding

1IntroductionMohonestimationplaysanimportantroleindigitalvideocompression.Block-matchingtechniquehasbeenadoptedinmanyvideocompressionstandardssuchasH.261,MPEG-l,MPEG-2andH.263.Eventhoughthealgorithmtoestimatethemotionvectorsisnotspecifiedexplicitly.However,despiteitssuccessfulapplications,itproducesarathernoisyinchonfield.Inverylowbit-ratevideocodingapplications,theamountofthesideinformationfortheinchonfieldrepresentsanimPOrtantportionofthetotalbit-rate.Therefore,motionestimatetechniques…     

An efficient gray search algorithm for the estimation of motionvectors

Motion vector estimation plays an important role in motion-compensated video coding. An efficient and fast search algorithm is proposed for the estimation of motion vectors. With the help of gray prediction, the algorithm can determine the motion vectors of image blocks quickly and correctly. Since the proposed algorithm performs better than other search algorithms [e.g. the three-step search (TSS), cross-search (CS), new three-step search (NTSS), four-step search (FSS), block-based gradient descent search (BBGDS), simple-and-efficient search (SES), prediction search (PS) and gray prediction search (GPS)], it is very beneficial in applications where the video coding speed is important