一种基于H.264的混合错误隐藏方法

随着基于H.264的视频传输业务越来越广泛的应用,针对视频传输的各种应用而进行的视频差错控制技术也逐渐成为研究的热点之一。针对网络中存在的各种误码问题,介绍了各种差错控制方法,并提出一种基于H.264的混合错误隐藏方法。该方法针对帧间预测块,采用时域错误隐藏和空域错误隐藏方法相结合的方式,将帧间受损宏块分割为4个8×8独立进行错误隐藏。利用JVT发布的JM测试模型进行的仿真结果表明,PSNR值较改进前提高约0·1~0·2db。     

面向立体视频传输的右视点图像错误隐藏

利用立体视频序列视点间相关性及单视点内相关性,提出了一种面向立体视频传输的错误隐藏算法.从基于H.264/AVC立体视频编码结构出发,推断出受损块的参考模式;然后基于出错块的内容特征,根据块视差活力度(TDA)或块运动活力度(TMA)的大小,内容自适应地选择恰当的视点间及时域错误隐藏方法对受损块进行错误掩盖.实验结果表...     

一种基于边缘判决的空域差错掩盖算法

提出了一种基于边缘判决的解码视频空域差错掩盖算法。该算法首先对丢失块邻域中的像素进行边缘检测,并对检测出的边缘判断其是否会穿过丢失块。然后使用方向选择过程提取多个候选插值方向,并通过边界像素灰度差决定最终插值方向。实验结果表明本算法有效地提高了错误图像的掩盖效果。     

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。     

Adaptive Pixel Interpolation for Spatial Error Concealment

Error concealment techniques are widely used as efficient ways to recover the lost information at the decoder. This paper proposes an adaptive pixel interpolation technique for spatial error concealment in the block based coding system. For a missing pixel in a corrupted block, its value is derived from four neighborhoods of the block through interpolation using multiple prediction strategy. The weighting rules of these four neighborhood blocks are carefully designed with regard to three factors, the distance to the missing pixels within the given corrupted block, the percentage of uncorrupted pixels, and the similarity to the given corrupted block. The proposed method works effectively in consecutive block loss situation, which is common in real applications of video transmission. Experimental results show the proposed technique gains more accurate recovery of the missing pixels than the existing schemes.     

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.     

Hybrid Temporal Error Concealment Methods for Block-Based Compressed Video Transmission

Boundary matching algorithm (BMA) and decoder motion vector estimation (DMVE) are two well-known temporal error concealment methods using the matching-based approach. In these two methods, the motion vector of each missing block is estimated by choosing one among candidate motion vectors which minimizes a sum of absolute differences (SAD) between boundary pixels of the corrupted macroblock. In general, the performance of DMVE is better than that of BMA. However, depending on the location or pattern of the corrupted block, BMA produces higher visual quality than DMVE. In this paper, we propose two types of hybrid error concealment methods; switching method and blending method. The switching method chooses one of two results obtained by BMA and DMVE based on the normalized SAD values. In the blending method, the weighted sum of the results concealed by the aforementioned two methods is utilized to improve the performance of error concealment. In order to reduce blocking artifacts further, the modified overlapped-block motion compensation is adaptively applied to the concealed blocks. Simulation results show that the proposed methods outperform other techniques in terms of subjective visual quality as well as PSNR performance.     

多向变长区间的空域内插错误掩盖技术

本文首先简要介绍几种空域错误掩盖技术,然后提出了多向变长区间的空域内插错误掩盖技术. 该技术是基于错误块邻域的边界特性选择空域内插方向和参考区域,使得掩盖的视频图像既保持了边界信息又减小无关区域的影响. 实验结果表明本文算法有效地提高了错误图像的掩盖效果.     

一种基于快速搜索的视频时域差错隐藏算法

为了克服视频传输中因传输差错引起的视频质量下降,提出一种基于快速搜索的边框匹配时域隐藏算法(CSBM)。该算法针对时域差错隐藏的运动矢量恢复问题,利用边框匹配算法改善被恢复的物体边缘模糊的情况;采用基于中心偏置的快速搜索样式得到最小边界匹配差值的候选运动矢量,减少了解码器差错恢复的计算复杂度。实验结果显示,针对不同性质的序列,该算法与边界匹配算法(SMA)、棱形搜索的边界匹配法(DSSM)等典型差错隐藏方法相比,平均搜索点数可减少12.5~19个点,亮度分量的峰值信噪比(PSNR)能改善0.93~1.55 dB,证明该算法能获得更好的差错隐藏效果,并减少了运算量。     

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     

A MODIFIED EDGE-ORIENTED SPATIAL INTERPOLATION ALGORITHM FOR CONSECUTIVE BLOCKS ERROR CONCEALMENT

This paper proposes a low-complexity spatial-domain Error Concealment （EC） algorithm for recovering consecutive blocks error in still images or Intra-coded （I） frames of video sequences. The proposed algorithm works with the following steps. Firstly the Sobel operator is performed on the top and bottom adjacent pixels to detect the most likely edge direction of current block area. After that one-Dimensional （1D） matching is used on the available block boundaries. Displacement between edge direction candidate and most likely edge direction is taken into consideration as an important factor to improve stability of 1D boundary matching. Then the corrupted pixels are recovered by linear weighting interpolation along the estimated edge direction. Finally the interpolated values are merged to get last recovered picture. Simulation results demonstrate that the proposed algorithms obtain good subjective quality and higher Peak Signal-to-Noise Ratio （PSNR） than the methods in literatures for most images.     

基于多方向自适应加权的空间错误隐藏算法

为了提高H.264/AVC压缩视频码流在无线信道传输过程中的抗误码性能,提出了一种基于多方向自适应加权的空间错误隐藏算法.该算法首先应用边缘算子检测受损宏块的相邻宏块信息,然后通过多方向自适应加权插值得到受损宏块像素近似值.实验表明,该算法相对传统空间错误隐藏算法,对于不同视频序列图像重构质量有很大的改善,具有较高的应用价值.     

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.     

Gravity direction-based ultra-fast intraprediction algorithm for H.264/AVC video coding

The H.264/AVC video coding standard uses in intraprediction, 9 directional modes for 4 × 4 and 8 × 8 luma blocks, and 4 directional modes for 16 × 16 luma macroblocks, and 8 × 8 chroma blocks. The use of the variable block size and multiple modes in intraprediction makes the intracoding of H.264/AVC very efficient compared with other compression standards; however, computational complexity is increased significantly. In this paper, we propose a fast mode selection algorithm for intracoding. This algorithm is based on the vector of the block’s gravity center whose direction is used to select the best candidate prediction mode for intracoding. On this basis, only a small number of intraprediction modes are chosen for rate distortion optimization (RDO) calculation. Different video sequences are used to test the performance of proposed method. The simulation results show that the proposed algorithm increases significantly the speed of intracoding with negligible loss of peak signal-to-noise ratio quality.     

High‐Performance Spatial and Temporal Error‐Concealment Algorithms for Block‐Based Video Coding Techniques

A compressed video bitstream is sensitive to errors that may severely degrade the reconstructed images even when the bit error rate is small. One approach to combat the impact of such errors is the use of error concealment at the decoder without increasing the bit rate or changing the encoder. For spatial‐error concealment, we propose a method featuring edge continuity and texture preservation as well as low computation to reconstruct more visually acceptable images. Aiming at temporal error concealment, we propose a two‐step algorithm based on block matching principles in which the assumption of smooth and uniform motion for some adjacent blocks is adopted. As simulation results show, the proposed spatial and temporal methods provide better reconstruction quality for damaged images than other methods.     

关于MPEG-2空域时域自适应错误隐藏算法

MPEG-2的压缩算法,由于采用可变字长编码使得其对信道错误十分敏感,即使单比特错误都有可能导致图像质量的严重下降,使部分或整条信息丢失。在解码端的错误隐藏技术是解决这个问题的有效方法之一。该文基于图像像素间的最大光滑连接,利用丢失宏块的邻域宏块的全部信息,导出了加权内插的错误隐藏公式。提出了一种自适应的错误隐藏方法,序列中的第一帧使用空域信息重构丢失的区域,其它帧使用本文建议的空域时域自适应错误隐藏方法。仿真实验的结果表明本文建议的算法优于一些传统算法。     

HEVC中基于前后景区域的错误隐藏

新一代视频编码标准HEVC采用四叉树编码结构,能够高效地进行视频编码,尤其适用于高清视频。然而,网络信道的不可靠性会导致视频数据的受损或丢失,HEVC的编码特性决定了视频数据的受损或丢失可能会发生在不同尺寸编码块中。因此,在分析各种不同尺寸编码块自身特性的基础上,提出首先对视频进行前景、后景区分,其中利用OBMA算法区分出边界处与运动物体,然后对于不同区域的错误块分别进行隐藏。     

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.     

An effective GM/LM-based video error concealment

Error concealment (EC) techniques are often utilized at decoder side to improve reconstructed videos, in case of some information is lost during transmission on a wireless or band-width limited communication channel. In this paper, a global motion/local motion (GM/LM)-based error concealment method is proposed. First, the correct-macro-blocks (CMBs) are classified into global motion compensated MBs and local motion compensated MBs adaptively. Then, an erroneous MB (EMB) is classified into one of the three types: global motion MB (GMB), local motion MB (LMB), and global/local overlapping MB (GLMB) according to the MB type information in its neighbors. For the EMB with its type, GMB is recovered using the global motion vector (GMV). The EMB with its type LMB is recovered using the average motion vector information. And for the MB with its type GLMB, a recursive boundary matching strategy is utilized to search an optimal recovering motion vector. Experimental results show the effectiveness of the proposed GM/LM-based error concealment method.     

An effective error concealment scheme for heavily corrupted H.264/AVC videos based on Kalman filtering

Error concealment at the decoder side is an economical approach to ensuring an acceptable and stable video quality in case of packet erasure or loss, and thus, it has attracted considerable research and application interest. Relevant techniques usually employ the spatial or temporal correlation to recover the motion vectors (MVs) of the missing blocks, and interpolation, extrapolation, or boundary-matching schemes are usually effective. However, for heavily corrupted sequences, e.g., with block loss rate beyond 50 %, most methods might perform less satisfactorily. Inspired by the tracking efficiency of Kalman filter (KF), in the present work, we adopted it to predict the missing MVs, and the unpredicted ones (minority) were restored complementarily using a modified bilinear motion field interpolation (MFI) method. Since the KF prediction is independent of the loss rate, the present framework proves to be robust for heavily corrupted videos. Experimental results on typical sequences reveal that the proposed algorithm outperforms the boundary-matching algorithm embedded in the H.264/AVC reference code, the MFI and the MV extrapolation techniques in the literature.