Distributed Video Coding Using LDPC Codes for Wireless Video

Popular video coding standards like H.264 and MPEG working on the principle of motion-compensated pre-dictive coding demand much of the computational resources at the encoder increasing its complexity. Such bulky encoders are not suitable for applications like wireless low power surveillance, multimedia sensor networks, wireless PC cameras, mobile camera phones etc. New video coding scheme based on the principle of distributed source coding is looked upon in this paper. This scheme supports a low complexity encoder, at the same time trying to achieve the rate distortion performance of conventional video codecs. Current im-plementation uses LDPC codes for syndrome coding.

Design of the Quantization Matrix in the Distributed Compressed Sensing Video Coding*

In the frame of compressed sensing distributed video coding, the design of the quantization matrix directly affects the reconstruction quality of the receiving terminal of the video. In this article, we present a new design method of the Gaussian quantization matrix adapting to the compressed sensing coding, for that the distribution of the parameters of the image is featured of the characteristic of approximately normal distribution after measured by compressive sensing. By this way, the parameters of a certain quantity of the image frames depending on the video sequences generated by the Gaussian quantization matrix possess certain adaptive capacity. By comparison with the plan of the traditional quantization, the quantization matrix presented in this article would improve the reconstruction quality of the video.

A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

Error concealment in pixel based Wyner-Ziv video coding

In the Wyner-Ziv(WZ) video coding paradigm, a virtual correlation channel is assumed between the quantized source and the side information(SI) at the decoder, and channel coding is applied to achieve compression. In this paper, errors caused by the virtual correlation channel are addressed and an error concealment approach is proposed for pixel-based WZ video coding. In the approach, errors after decoding are classified into two types. Type 1 errors are caused by residual bit errors after channel decoding, while type 2 errors are due to low quality of SI in part of a frame which causes SI not lying within the quantization bin of a decoded quantized pixel value. Two separate strategies are respectively designed to detect and conceal the two types of errors. Simulations are carried out and results are presented to demonstrate the effectiveness of the proposed approach.

A NEW APPROACH TO DVC COMBINED WITH ROI EXTRACTION AND RESIDUAL VIDEO CODING FOR MULTIMEDIA SENSOR NETWORKS

The Wyner-Ziv distributed video coding scheme is characterized for its intraframe encoder and interframe decoder which can also approach the efficiency of an interframe encoder-decoder system. In Wyner-Ziv residual coding of video, the residual of a frame with respect to a reference frame is Wyner-Ziv encoded, which can reduces the input entropy and leads to a higher coding efficiency than directly encoding the original frame. In this paper, we propose a new approach of residual coding combined with Region Of Interest (ROI) extraction. Experimental results show that, the proposed scheme achieves better rate-distortion performance compared to conventional Wyner-Ziv coding scheme.

Rate estimate for regular LDPCA codec in distributed video coding

Accumulated low density parity check （LDPCA） codec is proposed for DISCOVER project in distributed video coding （DVC）, which offers flexible coding rate. Although it can use feedback channel to adapt the rate to the correlation of the video, but in real applications, using feedback channel can not always be possible. To solve this problem, some researchers proposed estimating the code rate at the encoder but the performance was not very good. Based on their researches, this paper considers the impact of convergence rate for iteration on rate estimate, which can be calculated using its check matrix. As a pilot study, this paper pays attention to the regular LDPCA codec. At the same time, it considers the impact of deviation in the estimated crossover probability, which gives some constraints to rate estimate. In the experiment, the proposed algorithm can improve the rate-distortion performance by up to 1 dB-1.2 dB.

Wyner-Ziv视频编码中边信息生成算法研究

在Wyner-Ziv视频编码系统中,针对生成边信息容易出现块效应和重影现象的问题,提出了一种基于原始图像相关性的重叠块双向运动补偿算法。在编码端计算原始图像相关性,并将相关性数据发送到解码端辅助运动估计,得到较精确的运动矢量,最后通过重叠块双向运动补偿生成边信息。实验结果表明,与现有的双向运动补偿内插算法相比,提出的算法生成边信息的平均PSNR可以提高1.5~3dB,且边信息的主观质量也有明显改善。

基于变换域Wyner-Ziv视频编码的相关噪声模型

在Wyner-Ziv(WZ)视频编码中,原始WZ帧数据和边信息(Side information,SI)间相关噪声模型是影响编码效率的关键因素。现有文献通常认为边信息和当前解码WZ帧的概率分布近似符合零均值拉普拉斯分布。本文详细研究了变换域WZ帧与相应边信息的残差系数的分布关系,发现其残差变换后直流系数带统计分布相比零均值拉普拉斯分布存在一定偏差,且系数带的相关噪声分布随时间和空间变换。根据变换域残差系数的分布特征,提出了一种基于变换域的相关噪声分布模型及自适应参数估计算法,利用帧内插时前向和后向运动补偿帧变换残差,在解码端估计系数带的分布参数。实验结果表明该算法有效提高了WZ视频编码的编码效率。

A new encoder rate-allocation method for distributed video coding

Distributed video coding(DVC)is a new video coding architecture.Compared with traditional video coding schemes,DVC has a simple encoder and complex decoder,which makes it suitable for circumstances where the encoder equipments are simple but the decoder equipments are complex.Most of the existing DVC architectures use decoder rate allocation method with the help of feedback channel.According to the results of the current decoding round,the decoder informs the encoder by feedback channel whether more parity bits are needed.The use of feedback channel not only increases the system delay,but also limits the use of DVC to instances where there is no feedback channel.In this paper,we propose a novel encoder rate allocation method.First,the simple three-step motion estimation is introduced into the encoder to estimate the side information of the decoder,and then the number of parity bits the decoder needs for each bitplane is allocated at the encoder according to the difference of the estimated side information and the current Wyner-Ziv(WZ)frame.Experiment results indicate that the accuracy of the proposed method is 5.18%-52.93% higher than that of the method proposed by Morbee.

一种空间域Wyner-Ziv视频编码系统的性能改进算法

分布式视频编码是建立在Slepian-Wolf和Wyner-Ziv信息编码理论基础上的全新视频编码框架,具有编码复杂度低,编码效率较高,抗误码性能好的特点.本文首先简单介绍了一种典型的分布式视频编码实现方案——空间域Wyner-Ziv视频编码,随后提出一种空间域Wyner-Ziv视频编码系统的性能改进算法,该算法在不增加编码复杂度的基础上,在解码端利用双向运动估计预测获取更高质量的边信息,同时采用基于Huber-Markov随机场约束的联合迭代解码算法重建图像.实验结果表明,在相同的输出码流情况下,本文改进算法在解码端重建图像的峰值信噪比与空间域Wyner-Ziv视频编码算法相比平均提高2dB,并且主观效果有所改善.

基于高斯混合模型的Wyner-Ziv视频编码

针对现有Laplacian模型不能精确描述相关噪声分布,分布式视频编码(Distributed Video Coding,DVC)的率失真性能改善非常有限,文中提出一种基于高斯混合模型的分布式视频编码方法.首先分析了WZ帧与相应边信息之间相关噪声的统计特征,发现相关噪声信息的分布并不满足某种单峰分布,然后采用高斯混合模型(Gaussian Mixture Model,GMM)对噪声系数直方图进行拟合,提出基于样本特征的EM(Expectation Maximum)算法来估计模型参数.将提出的高斯混合相关噪声模型与相应的Laplacian模型进行比较,实验结果表明前者更能精确描述相关噪声的统计特征,基于该模型的DVC率失真性能优于基于Laplacian模型的DISCOVER方案,获得的平均增益接近1dB.

Wyner-Ziv视频编码中边信息估计算法改进

与传统视频编码方法相比,DVC(distributed video coding)在编码性能方面还存在着较大差距。边信息估计是其中的关键技术之一,在很大程度上决定着编码效率。为缩短性能差距,改善边信息估计效率,提出一种针对像素域Wyner-Ziv视频编码系统的改进算法,在解码端改善了关键帧之间的运动矢量获取以及采用重叠块运动补偿来生成边信息。通过对大量测试序列的实验,验证了改进算法的率失真性能得到改善。

变换域Wyner-Ziv视频编码的码率控制

为了降低变换域Wyner-Ziv视频编码的解码复杂度,利用信道相关特征量及系数带的时间相关性提出了一种有效的码率控制算法.该算法在编码端估计传送的最小码率块,并利用不同系数带的时间相关性及信道的平均反馈次数,对估计的最小码率进行调整,得到实际需要传送的初始码率,从而有效地控制解码反馈次数,降低系统延时和解码复杂度.实验结果表明,该算法在保证编码效率的同时可以大幅降低解码复杂度,最大可降低82%.

Wyner-Ziv视频系统中解码算法研究

首先简要介绍了一种典型的分布式视频编码-Wyner-Ziv视频编码。然后对Wyner-Ziv视频编码中边信息进行理论分析,随后给出了基于加权MAD准则的边信息估计算法和基于先验概率约束的联合解码算法。实验仿真结果表明,采用本文解码优化策略,在编码端相同输出码率情况下,重建解码图像的PSNR比原始算法平均提高1.5dB。

无反馈分布式视频编码中Wyner-Ziv帧的顽健重构算法

在无反馈分布式视频编码系统中,提出了一种Wyner-Ziv帧的顽健重构算法。针对比特面解码错误带来的视频质量下降问题,对DC系数和AC系数使用不同重构方法,特别是对于解码失败的DC系数量化值,利用编码端原始图像的相关信息自适应地调整边信息量化值和解码失败量化值对重构的贡献,从而完成重构。实验结果表明,与最小均方误差重构算法相比,该算法可以有效提高解码视频的平均PSNR(peak signal-to-noise ratio),且解码视频图像的主观质量有明显改善。

无反馈分布式视频编码中Wyner-Ziv帧码率控制算法

基于分布式视频编码系统,提出一种Wyner-Ziv帧的码率控制算法.首先,通过理论推导和实验,提出了针对Wyner-Ziv帧不同系数带的率失真估计模型,并通过训练学习的方法针对不同系数带分别确定模型参数;然后,使用提出的率失真模型估计当前帧的编码码率,并结合目标码率约束确定最优量化矩阵;最后,为每个比特面分配相应数目的校验位,完成LDPC编码并输出.实验结果表明,在相同目标码率下,与现有无反馈码率控制算法相比,使用本算法可提高解码恢复视频峰值信噪比0.3～1dB,且编码端运算复杂度增加很小.