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.     

一种基于DCT域的分布式视频编码

在简单介绍空域Wyner-Ziv分布式视频编码的基础上,给出了一种编码复杂度较低的基于交换域分布式视频编码方法.仿真结果表明此算法的编码性能优于空域Wyner-Ziv编码算法.     

基于变换域Wyner-Ziv视频编码的有效重建算法

为了减少分布式视频编码系统重建值与真实值之间误差,提出了基于变换域Wyner-Ziv视频编码最小均方误差(MMSE)重建的一种有效重建算法.该算法充分利用视频帧间相关性,对MMSE重建算法积分区间做出调整,当边信处于解码值对应量化区间之内时,在量化区闻内利用MMSE重建;当边信息处于解码值对应量化区间之外时,对量化区间做出调整,在改进后的区间利用MMSE重建.实验结果表明,与最佳重建最小均方误差重建算法相比,该算法可以有效提高解码视频的平均PSNR.     

一种基于变换域Wyner-Ziv视频编码的有效重建算法

为了减少分布式视频编码系统解码后重建值与真实值之间误差,提出了基于变换域Wyner-Ziv视频编码最小均方误差(MMSE)重建的一种新的有效重建算法。该算法充分利用视频帧间相关性,对MMSE重建算法积分区间做出调整,当边信处于解码值对应量化区间之内时,在量化区间内利用MMSE重建;当边信息处于解码值对应量化区间之外时,对量化区间做出调整,在改进后的区间利用MMSE重建。实验结果表明,与最佳重建最小均方误差重建算法相比,该算法可以有效提高解码视频的平均PSNR。     

分布式视频编码中拉普拉斯-柯西混合分布相关噪声模型研究

该文通过研究变换域分布式视频编码中原始Wyner-Ziv(WZ)帧与相应边信息的残差系数特性,发现大残差和小残差系数统计分布与传统的拉普拉斯分布存在一定偏差。为了减少这种差异,提出一种拉普拉斯-柯西混合分布(LCMD)相关噪声模型及其参数估计算法。该混合模型利用改进的拉普拉斯分布描述小残差系数的分布,采用柯西分布描述大残差系数。实验结果表明该文提出的混合模型能较精确地描述WZ帧和边信息间的残差系数分布,从而有效地改善了变换域分布式视频编码的率失真性能,并减少系统解码端计算复杂度。     

分布式视频编码技术的研究现状及其展望

分布式视频编码(DVC)是建立在多信源信息编码理论基础上的一种新的视频编码榧架。在对目前分布式编码文献进行分析和综合基础之上,本文首先阐述了分布式视频编码的理论基础和应用背景,然后分析介绍了目前几种典型的分布式编码算法,给出了空间域Wyner-Ziv视频编码和频域wyner-Ziv视频编码的仿真结果和分析,最后对当的影响分布式编码的几个关键问题进行剖析和展望。     

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码率分配算法研究

码率分配是无反馈分布式视频编码中的关键技术之一.本文研究编码端快速边信息生成方法,基于边信息和Wyner-Ziv帧各个位平面误码率,提出了一种编码端码率分配算法(Bitplane Error Probability based Encoder Rate Control,BEP_ERC).还提出在编码端精确估计拉普拉斯-柯西混合分布(Laplace-Cauchy Mixture Distribution,LCMD)模型参数α和μ的思想.实验表明本文算法与现有算法相比,率失真性能提升0.1～0.4dB,且降低了编码端计算复杂度.     

基于层修复技术的DVC鲁棒传输框架

针对分布式视频编码(DVC)系统鲁棒传输问题,设计了一种基于层修复的DVC系统传输框架。该传输框架首先对关键帧(K帧)同时采用高效视频编码(HEVC)帧内编码和Wyner-Ziv编码,并将校验信息(Wyner-Ziv码流)作为修复层码流存入缓存中。若当前关键帧有丢失,则向编码端请求该帧对应的层修复码流,在解码端对错误块进行修复,获得关键帧解码质量的提升。同时,研究了层修复码率估计算法,利用已成功解码的位平面辅助完成算法重建。实验结果表明,该传输框架利用关键帧的层修复码流对关键帧失真部分进行了修复,提高了关键帧质量,改善了边信息质量,实现了DVC的鲁棒传输。     

一种自适应视频水印检测算法

提出了一种空间域视频水印自适应检测算法，充分利用视频解码过程中提取的附加倍息，根据水印信息在视频编码过程的损失程度，对重建视频图像中的每个像素计算其可信度因子，并以此实现对传统相关检测算法的改进。该算法能够在既定的水印嵌入算法条件下，进一步提高系统提取和检测水印信息的精度。     

Cross-band noise model refinement for transform domain Wyner-Ziv video coding

Distributed Video Coding (DVC) is a new video coding paradigm, which mainly exploits the source statistics at the decoder based on the availability of decoder side information. One approach to DVC is feedback channel based Transform Domain Wyner-Ziv (TDWZ) video coding. The efficiency of current TDWZ video coding trails that of conventional video coding solutions, mainly due to the quality of side information, inaccurate noise modeling and loss in the final coding step. The major goal of this paper is to enhance the accuracy of the noise modeling, which is one of the most important aspects influencing the coding performance of DVC. A TDWZ video decoder with a novel cross-band based adaptive noise model is proposed, and a noise residue refinement scheme is introduced to successively update the estimated noise residue for noise modeling after each bit-plane. Experimental results show that the proposed noise model and noise residue refinement scheme can improve the rate-distortion (RD) performance of TDWZ video coding significantly. The quality of the side information modeling is also evaluated by a measure of the ideal code length.     

Perceptual-based distributed video coding

In this paper, we propose a perceptual-based distributed video coding (DVC) technique. Unlike traditional video codecs, DVC applies video prediction process at the decoder side using previously received frames. The predicted video frames (i.e., side information) contain prediction errors. The encoder then transmits error-correcting parity bits to the decoder to reconstruct the video frames from side information. However, channel codes based on i.i.d. noise models are not always efficient in correcting video prediction errors. In addition, some of the prediction errors do not cause perceptible visual distortions. From perceptual coding point of view, there is no need to correct such errors. This paper proposes a scheme for the decoder to perform perceptual quality analysis on the predicted side information. The decoder only requests parity bits to correct visually sensitive errors. More importantly, with the proposed technique, key frames can be encoded at higher rates while still maintaining consistent visual quality across the video sequence. As a result, even the objective PSNR measure of the decoded video sequence will increase too. Experimental results show that the proposed technique improves the R-D performance of a transform domain DVC codec both subjectively and objectively. Comparisons with a well-known DVC codec show that the proposed perceptual-based DVC coding scheme is very promising for distributed video coding framework.     

基于边信息的分布式视频压缩感知的残差重构

压缩感知(Compressed Sensing,CS)结合了视频信号的变换和信息压缩过程,为简化编码算法提供了一种新的解决思路.把分布式视频编码(DVC)和CS结合在一起,构建简单的视频编码框架,并利用原始视频帧与边信息之间的相关性进行残差重构,提出了一种基于边信息的分布式视频压缩感知编解码方案.此方法对关键帧采用传统的帧内编、解码;对非关键帧CS进行随机观测提取观测向量,解码端利用优化的边信息和传输的CS观测向量进行联合重构.实验结果表明,该方法在运动较平滑的序列中比参考方案的恢复质量提高了4 ～6 dB.     

Distributed video coding based on vector quantization: Application to capsule endoscopy

We present in this paper a new distributed video coding (DVC) architecture for wireless capsule endoscopy. It is based on the state of the art DVC systems, but without using key frames. Instead, it uses an adapted vector quantization (VQ) with a searching complexity that is shifted to the decoder. VQ allows creating a good side information (SI) by exploiting the similarities in human anatomy. Thus, SI is created from a codebook (CB) rather than by motion compensated prediction. This approach decreases largely the complexity of the encoder, which codes only Wyner-Ziv frames, and allows a progressive decoding. The encoder of the proposed DVC generates only a simple hash that is used by the decoder to select the corresponding VQ codeword. The obtained experimental results show that rate-distortion results are better than those of JPEG, and show the possibility of using scalable coding to control the used rate and energy.     

分布式视频编码边信息改进技术

高质量的边信息生成技术是分布式视频编码系统实现高压缩效率的关键所在.提出一种边信息的改进方法,对部分译码的Wyner-Ziv(WZ)帧中运动剧烈的区域进行空域修正,使用相邻关键帧对应块的空间预测值与实际值之间的差值来补偿当前部分译码WZ帧中空间预测的误差.仿真结果表明该方法提升了边信息的质量,进而提高了DVC系统的率失真性能.     

Deep chroma prediction of Wyner–Ziv frames in distributed video coding of wireless capsule endoscopy video

Compression of captured video frames is crucial for saving the power in wireless capsule endoscopy (WCE). A low complexity encoder is desired to limit the power consumption required for compressing the WCE video. Distributed video coding (DVC) technique is best suitable for designing a low complexity encoder. In this technique, frames captured in RGB colour space are converted into YCbCr colour space. Both Y and CbCr representing luma and chroma components of the Wyner–Ziv (WZ) frames are processed and encoded in existing DVC techniques proposed for WCE video compression. In the WCE video, consecutive frames exhibit more similarity in texture and colour properties. The proposed work uses these properties to present a method for processing and encoding only the luma component of a WZ frame. The chroma components of the WZ frame are predicted by an encoder–decoder based deep chroma prediction model at the decoder by matching luma and texture information of the keyframe and WZ frame. The proposed method reduces the computations required for encoding and transmitting of WZ chroma component. The results show that the proposed DVC with a deep chroma prediction model performs better when compared to motion JPEG and existing DVC systems for WCE at the reduced encoder complexity.     

Distributed Video Coding

Distributed coding is a new paradigm for video compression, based on Slepian and Wolf's and Wyner and Ziv's information-theoretic results from the 1970s. This paper reviews the recent development of practical distributed video coding schemes. Wyner-Ziv coding, i.e., lossy compression with receiver side information, enables low-complexity video encoding where the bulk of the computation is shifted to the decoder. Since the interframe dependence of the video sequence is exploited only at the decoder, an intraframe encoder can be combined with an interframe decoder. The rate-distortion performance is superior to conventional intraframe coding, but there is still a gap relative to conventional motion-compensated interframe coding. Wyner-Ziv coding is naturally robust against transmission errors and can be used for joint source-channel coding. A Wyner-Ziv MPEG encoder that protects the video waveform rather than the compressed bit stream achieves graceful degradation under deteriorating channel conditions without a layered signal representation.