H.264视频误码掩盖综述

在无线网络和因特网上传输视频，误码掩盖的问题越来越重要。回顾了文献中介绍的误码掩盖的方法。误码掩盖后处理利用图像和视频信号的相关特性，在解码端对丢失区域进行掩盖，并总结了空域、时域，以及时空结合的误码掩盖方法。     

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H.263视频解码的误码掩盖技术研究

本文提出了一种基于接收端像素域的误码掩盖算法,包括误码检测、重同步、误码定位和估计误码数据等四个环节。计算机模拟结果显示,经误码掩盖之后的图像质量有显著的改善     

一种新颖实用的交互式视频抗误码方法

本文提出一种新颖的交互式视频抗误码方法.首先,分析了块匹配运动补偿编码方法产生时域误码扩散的机理,然后,相应地提出了一种新颖的误码掩盖和防止误码扩散联合方法.实验结果表明,使用本文提出的交互式视频抗误码方法能够有效地抑制和防止误码的扩散,保证了恢复视频质量.另外,该算法与H.263+标准兼容,具有实用价值.     

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.     

H．264后处理误码掩盖技术

数字视频通信中往往会由于信道不理想等原因而产生误码,而且误码在空间和时间上的扩散会导致重建图像质量不同程度的下降.而误码掩盖技术就是用来改进重建视频质量的重要方法之一.文章论述了国内外误码掩盖技术的现状及其典型算法,分析了误码掩盖技术的应用范围和性能,最后指出误码掩盖技术的发展前景.     

视频通信中的误码掩盖技术初探

在数字视频通信中,由于信道不理想等原因容易产生误码,而且误码在空间和时间上的扩散会导致重建图像质量不同程度的下降。最近发展起来的误码掩盖技术就是用来解决这类问题、改进重建视频质量的重要方法之一。在简要介绍误码掩盖的基本原理和相关技术的基础上,着重分析了新近采用的几种误码掩盖方法的应用范围和性能,并指出了它们的发展前景。．     

一种基于多参考帧的时域误码掩盖算法

视频压缩码流对于信道误码十分敏感,可导致重建图像质量严重下降,在接收端就要使用误码掩盖技术对损坏的视频进行掩藏。文中提出一种基于多参考帧的时域误码掩盖算法,首先计算受损宏块的相邻块的运动矢量的均值,然后遍历所有参考帧得到待选的误码掩盖宏块,最后用外边界匹配算法找出替代受损宏块的宏块。研究结果表明,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。     

Error control and concealment for video communication: a review

The problem of error control and concealment in video communication is becoming increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks and the Internet. This paper reviews the techniques that have been developed for error control and concealment. These techniques are described in three categories according to the roles that the encoder and decoder play in the underlying approaches. Forward error concealment includes methods that add redundancy at the source end to enhance error resilience of the coded bit streams. Error concealment by postprocessing refers to operations at the decoder to recover the damaged areas based on characteristics of image and video signals. Last, interactive error concealment covers techniques that are dependent on a dialogue between the source and destination. Both current research activities and practice in international standards are covered     

Error concealment techniques for digital TV

Compressed video bitstreams are intended for real-time transmission over communication networks. Most of the video coding standards employ the temporal and spatial prediction structure to reduce the transmitted video data. Therefore, the coded video bitstreams are highly sensitive to information loss and channel errors. Even a single bit error can lead to disastrous quality degradation in both time and space. This quality deterioration is exacerbated when no error resilient coding mechanism is employed to protect coded video data against the error prone environments. Error concealment is a data recovery technique that enables the decoder to conceal effects of transmission errors by predicting the lost or corrupted video data from the previously reconstructed error-free information. Motion vector recovery and motion compensation with the estimated motion vector is a good approach to conceal the corrupted macroblock data. In this paper, we develop various error concealment algorithms based on motion vector recovery, and compare their performances to those of conventional error concealment methods.     

IP视频通信中的错误掩盖技术

当视频压缩数据在QoS(Quality of Service)不能保障的IP网络(如INTERNET)上传输时,必须考虑信道所引入错误的影响,错误掩盖是消除错误的重要方法.本文建议了一种能够保持图像边缘的空域错误掩盖算法,该算法适用于基于块的视频压缩编码标准,如MPEG 2、H.263等.该算法根据受损宏块邻近区域的边缘信息自适应地确定用于内插的像素的权值,实验证明该算法能够很好地保持边缘的连续性,达到了较好的图像掩盖效果.     

基于SUSAN算子的空域自适应错误隐藏算法

为了消除空域错误隐藏后出现的模糊和块效应,提出了基于SUSAN检测算子的空域自适应错误隐藏算法。算法首先利用SUSAN算子检测丢失宏块周围的边缘点,然后根据边缘点确定丢失宏块中边缘,最后根据边缘情况自适应地选择插值方法恢复丢失宏块。实验表明,丢失宏块边缘的检测受噪声影响很小,对孤立丢失块有较好的恢复效果且计算量较小。与传统空域错误隐藏算法相比,本文算法的峰值信噪比PSNR能提高大约1～3dB。     

Error concealment analysis for H.264/advanced video coding encoded video sequences

Error concealment methods have become very important in particular when transmitting video streams over error prone wireless links. Often a retransmission of corrupted sequences is not possible and thus the receiver has to make the best out of the received stream. The contributions of this article are the following: firstly, a performance comparison of various error concealment strategies (straight decoding, slice level concealment and macroblock level concealment) is presented based on the detection of errors, the exact location of which is unknown. Secondly, an analytical treatment of the slice level concealment, resulting in a precise mathematical model is provided. Finally, further improvements are proposed by subjective methods based on visual inspection and comparison of their performance by means of simulations.     

基于3D视频的错误隐藏技术分析

随着3D视频产品的逐步问世,3D视频技术逐渐成为当前研究的热点。由于3D视频编码是利用多个视点的空间、时间及视点间的相关性进行压缩编码,导致当3D视频遭遇不可靠信道差错时,其受损的影响比传统的2D视频更严重。因此,研究基于3D视频的差错控制技术十分必要,针对3D视频的3种视频格式,初步探讨了目前已经出现或正在研究中的错误隐藏技术。     

Concealment of damaged block transform coded images usingprojections onto convex sets

An algorithm for lost signal restoration in block-based still image and video sequence coding is presented. Problems arising from imperfect transmission of block-coded images result in lost blocks. The resulting image is flawed by the absence of square pixel regions that are notably perceived by human vision, even in real-time video sequences. Error concealment is aimed at masking the effect of missing blocks by use of temporal or spatial interpolation to create a subjectively acceptable approximation to the true error-free image. This paper presents a spatial interpolation algorithm that addresses concealment of lost image blocks using only intra-frame information. It attempts to utilize spatially correlated edge information from a large local neighborhood of surrounding pixels to restore missing blocks. The algorithm is a Gerchberg (1974) type spatial domain/spectral domain constraint-satisfying iterative process, and may be viewed as an alternating projections onto convex sets method.