Multiple side information streams for distributed video coding

An improved Wyner-Ziv decoder for distributed video coding (DVC) is proposed, which uses multiple side information streams obtained by using multiple reference frames. Simulation results show that the proposed algorithm can achieve a significant PSNR gain of up to 2.4 dB over the best available DVC codec at the same bit rate     

An improved side information generation for distributed video coding

This paper presents a side information (SI) scheme for distributed video coding based on multilayer perceptron. The suggested scheme predicts a Wyner–Ziv (WZ) frame from two decoded key frames. The network is trained offline using patterns from different standard video sequences with varied motion characteristics to achieve generalization. The proposed scheme is simulated along with other standard video coding schemes. Performance comparisons have been made with respect to training convergence, rate distortion (RD), peak signal to noise ratio (PSNR), number of requests per SI frame, decoding time requirement, etc. In general, it is observed that the proposed scheme has a superior SI frame generation capability as compared to its competent schemes.     

Low complexity distributed video coding

ContextConventional video encoding is a computationally intensive process that requires a lot of computing resources, power and memory. Such codecs cannot be deployed in remote sensors that are constrained in terms of power, memory and computational capabilities. For such applications, distributed video coding might hold the answer.ObjectiveIn this paper, we propose a distributed video coding (DVC) architecture that adheres to the principles of DVC by shifting the computational complexity from the encoder to the decoder and caters to low-motion scenarios like video conferencing and surveillance of hallways and buildings.MethodThe architecture presented is block-based and introduces a simple yet effective classification scheme that aims at maximizing the use of skip blocks to exploit temporal correlation between consecutive frames. In addition to the skip blocks, a dynamic GOP size control algorithm is proposed that instantaneously alters the GOP size in response to the video statistics without causing any latency and without the need to buffer additional frames at the encoder. To facilitate real-time video delivery and consumption, iterative channel codes like low density parity check codes and turbo codes are not used and in their place a Bose–Chaudhuri–Hocquenghem (BCH) code with encoder rate control is used.ResultsIn spite of reducing the complexity and eliminating the feedback channel, the proposed architecture can match and even surpass the performance of current DVC systems making it a viable solution as a codec for low-motion scenarios.ConclusionWe conclude that the proposed architecture is a suitable solution for applications that require real-time, low bit rate video transmission but have constrained resources and cannot support the complex conventional video encoding solutions.Practical implicationsThe practical implications of the proposed DVC architecture include deployment in remote video sensors like hallway and building surveillance, video conferencing, video sensors that are deployed in remote regions (wildlife surveillance applications), and capsule endoscopy.     

Improved side information generation algorithm for Wyner-Ziv video coding简

Side information has a significant influence on the rate-distortion（RD） performance of distributed video coding（DVC）. In the conventional motion compensated frame interpolation scheme, all blocks adopt the same side-information generation method regardless of the motion intensity inequality at different regions. In this paper, an improved method is proposed. The image blocks are classified into two modes, fast motion and slow motion, by simply computing the discrete cosine transformation（DCT） coefficients at the encoder. On the decoder, it chooses the direct interpolation and refined motion compensated interpolation correspondingly to generate side information. Experimental results show that the proposed method, without increasing the encoder complexity, can increase the average peak signal-to-noise ratio（PSNR） by up to 1~ 2 dB compared with the existing algorithm. Meanwhile, the proposed algorithm significantly improves the subjective quality of the side information.     

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.     

Side information generation with auto regressive model for low-delay distributed video coding

In this paper, we propose an auto regressive (AR) model to generate the high quality side information (SI) for Wyner-Ziv (WZ) frames in low-delay distributed video coding, where the future frames are not used for generating SI. In the proposed AR model, the SI of each pixel within the current WZ frame t is generated as a linear weighted summation of the pixels within a window in the previous reconstructed WZ/Key frame t − 1 along the motion trajectory. To obtain accurate SI, the AR model is used in both temporal directions in the reconstructed WZ/Key frames t − 1 and t − 2, and then the regression results are fused with traditional extrapolation result based on a probability model. In each temporal direction, a weighting coefficient set is computed by the least mean square method for each block in the current WZ frame t. In particular, due to the unavailability of future frames in low-delay distributed video coding, a centrosymmetric rearrangement is proposed for pixel generation in the backward direction. Various experimental results demonstrate that the proposed model is able to achieve a higher performance compared to the existing SI generation methods.     

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.     

Side information estimation and new symmetric schemes for multi-view distributed video coding

This paper deals with distributed video coding (DVC) for multi-view sequences. DVC of multi-view sequences is a recent field of research, with huge potential impact in applications such as videosurveillance, real-time event streaming from multiple cameras, and, in general, immersive communications. It raises however several problems, and in this paper we tackle two of them. Based on the principles of Wyner–Ziv (WZ) coding, in multi-view DVC many estimations can be generated in order to create the side information (SI) at the decoder. It has been shown that the quality of the SI strongly influences the global coding performances. Therefore, this paper proposes to study the contribution of multiple SI estimations (in the temporal and view directions) to the global performances. Moreover, we propose new symmetric schemes for longer group of pictures (GOP) in multi-view DVC and show that we can further exploit the long-term correlations using a new kind of estimation, called diagonal. For such schemes, several decoding strategies may be envisaged. We perform a theoretical study of the temporal and inter-view dependencies, and confirm by experiments the conclusion about the best decoding strategy.     

Low bitrate video coding with depth compensation

A depth-compensated low bitrate hybrid video coder for videophone applications is described. Depth and associated position information is extracted from the video frames using an edge-based stereo algorithm. A global motion vector and scale factor are extracted from the depth map and used as parameters for a model of the moving object. These global parameters are used to make the motion-compensated prediction more effective, by compensating for the change in size of the object. Simulations show that the compensated coder results in coded sequences with SNRs up to 1 dB better than those coded with conventional hybrid coders, at a coding rate of 64 kbit/s     

Channel simulation and coding with side information

Studies the minimum random bit rate required to simulate a random system (channel), where the simulator operates with a given external input. As measures of simulation accuracy the authors use both the variational distance and the d¯ distance between joint input-output distributions. They find the asymptotic number of random bits per input sample required for accurate simulation, as a function of the distribution of the input process. These results hold for arbitrary channels and input processes, including nonstationary and nonergodic processes and do not hinge on a specific simulation scheme. A by-product of the analysis is a general formula for the minimal achievable source coding rate with side information     

Introducing skip mode in distributed video coding

Although it was proven in the 1970s already by Wyner and Ziv and Slepian and Wolf that, under certain conditions, the same rate–distortion boundaries exist for distributed video coding (DVC) systems as for traditional predicting systems, until now no practical DVC system has been developed that even comes close to the performance of state-of-the-art video codecs such as H.264/AVC in terms of rate–distortion. Some important factors for this are the lower accuracy of the motion estimation performed at the decoder, the inaccurate modeling of the correlation between the side information and the original frame, and the absence in most state-of-the-art DVC systems of anything conceptually similar to the notion of skipped macroblocks in predictive coding systems.This paper proposes an extension of a state-of-the-art transform domain residual DVC system with an implementation of skip mode. The skip mode has an impact at two different places: in the turbo decoder, more specifically the soft input, soft output (SISO) convolutional decoder, and in the puncturing of the parity bits. Results show average bitrate gains up to 39% (depending on the sequence) achieved by combining both approaches.Furthermore, a hybrid video codec is presented where the motion estimation task is shifted back to the encoder. This results in a drastic increase in encoder complexity, but also in a drastic performance gain in terms of rate–distortion, with average bitrate savings up to 60% relative to the distributed video codec. In the hybrid video codec, smaller but still important average bitrate gains are achieved by implementing skip mode: up to 24%.     

Low bit-rate video coding with spatio-temporal geometric transforms

A low bit-rate video coding technique that uses spatio-temporal geometric transforms is presented. Motion compensation based on the bilinear transform is employed to reduce the temporal redundancy of the video. The spatial redundancy of the motion compensated error images is reduced by a combination of fractals and the DCT. It is shown that in the objects boundaries of the motion compensated error image fractals outperforms the DCT, while in the smooth areas the DCT is better than fractals. A hybrid combination of fractals and the DCT gives the best result. The performance of this hybrid codec with geometrically transformed motion compensation is compared against the H.261 standard video codec at 64 kbit/s     

On zero-error source coding with decoder side information

Let (X,Y) be a pair of random variables distributed over a finite product set V/spl times/W according to a probability distribution P(x,y). The following source coding problem is considered: the encoder knows X, while the decoder knows Y and wants to learn X without error. The minimum zero-error asymptotic rate of transmission is shown to be the complementary graph entropy of an associated graph. Thus, previous results in the literature provide upper and lower bounds for this minimum rate (further, these bounds are tight for the important class of perfect graphs). The algorithmic aspects of instantaneous code design are considered next. It is shown that optimal code design is NP-hard. An optimal code design algorithm is derived. Polynomial-time suboptimal algorithms are also presented, and their average and worst case performance guarantees are established.     

Source coding with side information at several decoders

A source coding problem is considered which generalizes source coding with side information [1], [2]. Three correlated information sourcesX,YandZ, are block-encoded:Yis to be reconstructed by two different decoders, one having access to the encoded version ofXand the other having access to the encoded version ofZ. The region of achievable rates is determined, assuming that thc sources are discrete, memoryless, and stationary. The resuit is generalized to an arbitrary finite number of decoders.     

Side information refinement using motion estimation in dc domain for transform-based distributed video coding

The key to good decoding performance in distributed video coding systems lies in the efficient prediction of frames using side information. Previously, this process has been performed without considering the progressive nature of the synthesis of the final frame. Observing the fact that incorrectly predicted areas of the current frame can be detected at different levels of final frame synthesis, an algorithm is proposed for refinement of side information synthesis based on an additional stage of motion estimation. The additional stage is performed on correctly decoded DC frames and is used to significantly improve the motion prediction of the final resolution frames, which leads to enhanced performance of the overall system.     

CDV-DVC: Transform-domain distributed video coding with multiple channel division

This paper proposes an efficient distributed coding system based on multiple channel division. We develop the hierarchical motion refinement scheme using DC syndrome bits to generate high quality side information (SI) for Wyner–Ziv (WZ) frames. Moreover, we estimate local distortion characteristics of an SI frame and encode the SI frame in three coding modes: skip mode for the reliable channel, WZ mode for the medium channel, and intra mode for the unreliable channel. No bit is transmitted in the skip mode. Syndrome bits in the WZ mode are adaptively allocated based on the local distortion characteristics. The H.264 intra coding is performed in the intra mode to recover severely erroneous blocks. Experimental results show that the proposed algorithm provides significantly better rate-distortion performance than the state-of-the-art DISCOVER codec.     

Independent key frame coding using correlated pixels in distributed video coding

A novel intra-coding technique is proposed that eliminates the requirement of a secondary coding scheme for coding the key frames in distributed video coding (DVC). The proposed technique uses the Slepian-Wolf theorem and Wyner-Ziv (WZ) coding with spatially predicted information to transmit the key-frames to the DVC decoder. Simulation results show that the proposed WZ-intra coding technique (WZ-I) can achieve up to 5 dB PSNR gain compared to MPEG-2 intra coding (MPEG-I) at the same bit rate with negligible computational cost to the encoder     

Nonlinear quantisation for pixel domain distributed video coding

A nonlinear quantisation algorithm for pixel domain distributed video codec (DVC) is proposed. A residual signal is generated at the encoder considering the Wyner-Ziv frame to be encoded and adjacent reference frames and this residual signal is quantised using a nonlinear quantiser. The proposed algorithm is simulated for a number of test video sequences and the results depict a significant improvement of rate distortion performance, by reducing the bit rate while keeping the same PSNR when compared with available pixel domain DVC codec that uses a linear quantiser.     

无反馈分布式视频编码中的速率控制算法

针对现有比特平面级编码端速率控制算法估计精度要求高的问题,提出了一种帧级编码端速率控制算法。该算法通过在编码端利用分层快速运动补偿内插产生高质量的边信息估计,并根据循环移位去除比特平面间的级别性,使每个比特平面的编码速率均匀化,从而实现帧级别的速率控制。实验结果表明,与现有算法相比,所提算法对中高速运动视频边信息估计质量有明显提升,且解码视频的平均PSNR(peak signal-to-noise ratio)均有提高。