基于块运动变形的时域差错掩盖

传统的时域差错掩盖技术通常将宏块作为整体考虑,没有具体分析受损宏块的运动特征,当受损宏块具有复杂剧烈的运动时掩盖效果不理想.通过对受损宏块的运动特征认真研究,提出了基于块变形的时域差错掩盖算法.算法充分利用受损宏块的周围信息将宏块运动划分成多种运动情况,针对不同运动情况采取不同的掩盖策略.在确定某受损块存在块变形运动时实施块变形掩盖,并通过合理的变形区域选择保证块变形的合理性.基于H.263 的GOB交织打包仿真实验表明,提出算法对存在复杂剧烈运动的宏块掩盖效果良好,与BM和MFI-BM掩盖相比,掩盖后的主客观视频质量有显著的改善.     

低复杂度空域错误隐藏算法

在无线网等不可靠信道传输视频中,针对包含边缘信息的宏块丢失带来的错误,提出了一种低复杂度的空间域错误隐藏算法,该算法根据周围已经接收到的宏块特征,估算丢失宏块中边缘方向,并按照边缘方向使用周围临近像素值进行插值,恢复出包含边缘的宏块;在插值过程中提出并采用了一种快捷的方向插值法。实验结果表明,该算法能有效地掩盖丢失宏块,比常规方法具有更好的掩盖效果与实时性。     

Error detection based on MB types

This paper proposes a method of error detection based on macroblock （MB） types for video transmission. For decoded inter MBs, the absolute values of received residues are accumulated. At the same time, the intra textural complexity of the current MB is estimated by that of the motion compensated reference block. We compare the inter residue with the intra textural complexity. If the inter residue is larger than the intra textural complexity by a predefined threshold, the MB is considered to be erroneous and errors are concealed. For decoded intra MBs, the connective smoothness of the current MB with neighboring MBs is tested to find erroneous MBs. Simulation results show that the new method can remove those seriously-corrupted MBs efficiently. Combined with error concealment, the new method improves the recovered quality at the decoder by about 0.5--1 dB.     

基于自适应叠加的H.264时域错误隐藏算法

为了减小视频传输错误对解码端重建视频质量的影响,根据H.264标准的特点,提出一种基于多模式自适应叠加的时域错误隐藏算法。该算法以不同分割模式对丢失宏块进行4次隐藏,得到4个隐藏块,并计算各模式的绝对帧差和,使该值最小的2个隐藏块自适应加权叠加作为最终的替代块。仿真结果表明,与传统方法相比,该算法的错误隐藏性能得到较大提高。     

高效的I帧分区错误隐藏方法

针对现有I帧错误隐藏方法不能平衡恢复图像质量与算法复杂度的问题,提出了一种高效的I帧分区错误隐藏方法。首先,利用视频帧之间的运动相关性将丢失宏块分为运动宏块和静止宏块。对于静止宏块,采用帧拷贝法进行掩盖;对于运动宏块,再根据其周围正确解码宏块的纹理信息将其分为平滑块和纹理块。对平滑块采用双线性插值法进行恢复;对纹理块利用比较精细的指数分布权重的加权模板匹配(WTE)法进行掩盖。实验结果表明,与WTE算法相比,所提方法的峰值信噪比(PSNR)平均提高了2.6 dB,计算复杂度平均降低了90%。对于场景连续的具有不同特征和分辨率的视频序列,所提方法都具有一定的适用性。     

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H.264的误码隐藏技术

为了在高误码环境下提高视频通信质量,提出一种改进的基于H.264的误码隐藏技术。对于帧内编码图像,根据图像直方图信息计算图像的光滑特性,然后自适应地选择线性插值的方法。对于帧间编码图像,根据不同大小块编码类型和多参考帧的特性,能够更准确地估计出丢失的MV,进行时域误码隐藏。实验表明,此方法同H.264参考软件JM11.0方法相比,具有更好的主客观图像恢复质量。     

Spatial error concealment for stereoscopic video coding based on pixel matching

In stereoscopic video coding, the interview correlation between the stereo image pair can be used for error concealment. A new spatial error concealment method for stereoscopic video coding based on pixel matching in the decoder is proposed in this paper. The lost macroblocks are recovered by utilizing disparity matching between two-view images on a pixel-by-pixel basis. Firstly, we get the candidate disparity vectors of the four neighboring pixels of the lost pixel by disparity matching in the decoder. Secondly, by calculating the boundary pixel difference, we determine an optimal replacing pixel in the reference image, and then we recover the lost pixel by the optimal pixel in the reference image. Experimental results show that the proposed algorithm performs better comparing to the previous technique.     

基于分块模式和双模式叠加的时域错误隐藏

为了减小视频传输中错误的影响,提高解码端重建视频质量,根据H.264/AVC标准的特点,提出了一种基于宏块分块模式预测和双模式叠加的时域错误隐藏方法.方法先对受损宏块进行宏块级运动补偿和残差修复,得到宏块级隐藏结果;然后利用受损宏块邻块分块模式和边缘特点预测受损宏块分块模式,分模式进行子块运动矢量估计和补偿;最后将宏块...     

Hybrid error concealments based on block content

We present a novel error-concealment method for MPEG-2 video decoders. Imperfect transmission of block-based compressed images may result in the loss of blocks, degrading the quality of the received video signal. Since an I-picture is used as a reference picture for forward and backward predictions of neighbouring pictures, transmission errors in an I-picture are propagated both spatially in the I-picture and temporally to P-/B-pictures, and thus may severely degrade the video signal, compared with the errors in P-/B-pictures. To minimise the quality degradation of the video signal, error concealment has been performed in I-pictures through adaptive spatial and temporal interpolations in the respective domains. Using edge information extracted from the neighbourhoods of the erroneous macroblocks, we categorise each erroneous macroblock (MB) based on the characteristics of neighbouring MBs. The categorised MB is reconstructed by the spatial or temporal error concealment methods selected by the category-dependent criteria reflecting the properties of the block content. The proposed technique solves blocky artefacts and blurring problems of existing error concealment methods and thus effectively conceals the lost blocks in an error video signal. Through computer simulations on damaged images, we show that the proposed method is robust to image characteristics and obtains better subjective quality than other error concealment methods.     

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.     

一种基于块匹配的立体视频错误隐藏方法*

提出了一种基于块匹配的立体视频错误隐藏方法,充分利用了空间相关性及左右视点间的视差信息的相关性.实验结果表明所提方法有较好的错误隐藏性能.     

Content-based hybrid error concealment approach for packet video communication over the noisy channels

Video compression makes the encoded video stream more vulnerable to the channel errors so that, the quality of the received video is exposed to severe degradation when the compressed video is transmitted over the error-prone environments. Therefore, it is necessary to apply error concealment (EC) techniques in the decoder to improve the quality of the received video. In this regard, an Adaptive Content-based EC Approach (ACBECA) is proposed in this paper, which exploits both the spatial and temporal correlations within the video sequences for the EC purpose. The proposed approach adaptively utilizes two EC techniques, including new spatial-temporal error concealment (STEC) technique, and a temporal error concealment (TEC) technique, to recover the lost regions of the frame. The STEC technique proposed in this paper is established on the basis of non-Local Means concept and tries to recover each lost macroblock (MB) as the weighted average of the similar MBs in the reference frame, whereas the TEC technique recovers the motion vector of the lost MB adaptively by analyzing the behavior of the MB in the frame. The decision on temporally or spatially reconstructing the degraded frames is made dynamically according to the content of the degraded frame (i.e., structure or texture), type of the error and also block loss rate (BLR). Compared with the state-of-the-art EC techniques, the simulation results indicate the superiority of the ACBECA in terms of both the objective and subjective quality assessments.

     

全局运动补偿技术在形状信息错误隐藏中研究

深入研究MPEG-4的形状编码技术和视频图像帧的编码方式,参照全局运动补偿技术,在图像形状信息全部丢失、部分丢失信息变化复杂的情况下,提出一种基于全局运动补偿的前向错误隐藏方法对出现传输错误的图像进行恢复。通过与Cheng方法对比仿真实验证明该方法取得很好的恢复效果,尤其是对象形状信息全部丢失时。     

基于AVS-P2的自适应时空域错误隐藏方法

错误隐藏技术是视频传输中保证重建质量的重要技术,可以有效恢复传输过程中因传输环境恶劣等原因造成的信息丢失和错误,为了增强AVS-P2的抗传输差错能力,提出了一种基于冗余运动矢量的自适应时空域错误隐藏算法。对I帧中的受损宏块采用空域错误隐藏方法,利用受损宏块周围已正确解码像素值进行加权插值来恢复;而对非I帧中的受损宏块则采用时域错误隐藏方法,根据宏块的运动剧烈程度分别选择AVS-P2中通用的错误隐藏方法和基于冗余运动矢量的错误隐藏方法。最后,在AVS-P2 RM52_20080721平台上实现了该算法,大量仿真实验结果表明,所提方法相比原有方法,解码视频图像的客观质量和主观效果均得到了一定提升。因此,所提方法可以有效保证AVS-P2解码端接收视频的主观质量,增强了其抗传输差错能力。     

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。     

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。     

IP网络MPEG-4视频流的自适应差错掩盖算法

针对IP网络上的MPEG-4视频传输,采用面向差错控制的打包方案,提出了一种结合时域差错恢复和空域差错恢复方法的快速自适应差错恢复混合算法。该算法根据视频帧的编码模式、丢失宏块的邻域宏块的编码模式、运动程度和运动矢量一致性自适应地选择差错恢复方法。仿真实验结果验证了自适应算法具有较好的差错恢复能力。     

Motion characteristic differentiated error concealment

In this paper, we propose a brand-new motion characteristic differentiated error concealment (MDEC) method based on motion field transfer. Firstly, the FMO checkerboard pattern is used at the encoder, so as to prevent MBs of a large area getting lost. Then at the decoder, Greedy Spread Motion Region Extraction (GSMRE) method is used to distinguish low-motion region from high-motion region in each frame based on different motion characteristic, and apply different strategies to recover regions with different characteristics respectively. Simulation results show that the proposed algorithm reconstructs the lost frame with both a better visual quality and a higher PSNR, comparing to error concealment methods including Joint Model, boundary matching, inpainting, and block motion vector extrapolation as well. For example, the PSNR gain of our approach over boundary matching algorithm reached about 0.6 dB, and 1.4 dB when the packet loss rate is 3 and 7%, respectively, which demonstrates that our method has an good application within a wide scope of packet loss rate.