Turbo trellis coded modulation for transform domain distributed video coding

A transform domain distributed video coding (DVC) codec is proposed using turbo trellis coded modulation (TTCM). TTCM symbols are generated at the DVC decoder using the side information and the parity bits received from the DVC encoder. These generated symbols are used at the TTCM-based DVC decoder to decode the bit stream. Simulation results show that a significant rate-distortion performance gain can be achieved using the proposed codec compared to the best state-of-the-art transform domain DVC codecs discussed in the literature.     

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     

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     

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.     

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.     

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.     

Advanced side information creation techniques and framework for Wyner–Ziv video coding

Recently, several distributed video coding (DVC) solutions based on the distributed source coding (DSC) paradigm have appeared in the literature. Wyner–Ziv (WZ) video coding, a particular case of DVC where side information is made available at the decoder, enable to achieve a flexible distribution of the computational complexity between the encoder and decoder, promising to fulfill novel requirements from applications such as video surveillance, sensor networks and mobile camera phones. The quality of the side information at the decoder has a critical role in determining the WZ video coding rate-distortion (RD) performance, notably to raise it to a level as close as possible to the RD performance of standard predictive video coding schemes. Towards this target, efficient motion search algorithms for powerful frame interpolation are much needed at the decoder. In this paper, the RD performance of a Wyner–Ziv video codec is improved by using novel, advanced motion compensated frame interpolation techniques to generate the side information. The development of these type of side information estimators is a difficult problem in WZ video coding, especially because the decoder only has available some reference, decoded frames. Based on the regularization of the motion field, novel side information creation techniques are proposed in this paper along with a new frame interpolation framework able to generate higher quality side information at the decoder. To illustrate the RD performance improvements, this novel side information creation framework has been integrated in a transform domain turbo coding based Wyner–Ziv video codec. Experimental results show that the novel side information creation solution leads to better RD performance than available state-of-the-art side information estimators, with improvements up to 2 dB; moreover, it allows outperforming H.264/AVC Intra by up to 3 dB with a lower encoding complexity.     

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%.     

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.     

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.     

Perceptually driven video error protection using a distributed source coding approach

In video communication systems, the video signals are typically compressed and sent to the decoder through an error-prone transmission channel that may corrupt the compressed signal, causing the degradation of the final decoded video quality. In this context, it is possible to enhance the error resilience of typical predictive video coding schemes using as inspiration principles and tools from an alternative video coding approach, the so-called Distributed Video Coding (DVC), based on the Distributed Source Coding (DSC) theory. Further improvements in the decoded video quality after error-prone transmission may also be obtained by considering the perceptual relevance of the video content, as distortions occurring in different regions of a picture have a different impact on the user's final experience. In this context, this paper proposes a Perceptually Driven Error Protection (PDEP) video coding solution that enhances the error resilience of a state-of-the-art H.264/AVC predictive video codec using DSC principles and perceptual considerations. To increase the H.264/AVC error resilience performance, the main technical novelties brought by the proposed video coding solution are: (i) design of an improved compressed domain perceptual classification mechanism; (ii) design of an improved transcoding tool for the DSC-based protection mechanism; and (iii) integration of a perceptual classification mechanism in an H.264/AVC compliant codec with a DSC-based error protection mechanism. The performance results obtained show that the proposed PDEP video codec provides a better performing alternative to traditional error protection video coding schemes, notably Forward Error Correction (FEC)-based schemes.     

Robust Video Transmission With Distributed Source Coded Auxiliary Channel

We propose a novel solution to the problem of robust, low-latency video transmission over lossy channels. Predictive video codecs, such as MPEG and H.26x, are very susceptible to prediction mismatch between encoder and decoder or “drift” when there are packet losses. These mismatches lead to a significant degradation in the decoded quality. To address this problem, we propose an auxiliary codec system that sends additional information alongside an MPEG or H.26x compressed video stream to correct for errors in decoded frames and mitigate drift. The proposed system is based on the principles of distributed source coding and uses the (possibly erroneous) MPEG/H.26x decoder reconstruction as side information at the auxiliary decoder. The distributed source coding framework depends upon knowing the statistical dependency (or correlation) between the source and the side information. We propose a recursive algorithm to analytically track the correlation between the original source frame and the erroneous MPEG/H.26x decoded frame. Finally, we propose a rate-distortion optimization scheme to allocate the rate used by the auxiliary encoder among the encoding blocks within a video frame. We implement the proposed system and present extensive simulation results that demonstrate significant gains in performance both visually and objectively (on the order of 2 dB in PSNR over forward error correction based solutions and 1.5 dB in PSNR over intrarefresh based solutions for typical scenarios) under tight latency constraints.      

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.     

分布式压缩视频编码的帧分类重构方法研究

在很多的应用场景中需要具有低复杂度的视频编码器,新兴的分布式视频编码和压缩感知技术正好适用于这些场景中,因而出现了一种新的视频编码方案——分布式压缩视频编码。在现有的一些分布式压缩视频编码方案中,视频帧在编码端是独立编码,在解码端进行联合解码,具体来说就是关键帧独立解码,非关键帧在由关键帧生成的边信息的帮助下进行解码,这就忽略了非关键帧之间的相关性。本文提出一个新的分布式视频编码方案,将非关键帧分为主非关键帧和次非关键帧,主非关键帧利用关键帧生成地边信息进行解码,而次非关键帧先利用相邻的主非关键帧进行观测值预测,然后再利用关键帧生成的边信息进行解码。实验结果表明,在本文提出的框架下,非关键帧的重构质量提高了有2dB~4dB。      

An efficient motion vector coding scheme based on minimum bitrateprediction

Motion vector coding efficiency is becoming an important issue in low bitrate video coding because of its increasing relative bit portion. This work presents a new motion vector coding technique based on minimum bitrate prediction. In the proposed scheme, a predicted motion vector is chosen from the three causal neighboring motion vectors so that it can produce a minimum bitrate in motion vector difference coding. Then the prediction error, or motion vector difference (MVD), and the mode information (MODE) for determining the predicted motion vector at a decoder are coded and transmitted in order. Sending bits for the MVD ahead of bits for the MODE, the scheme can minimize the bit amount for the MODE by taking advantage of the fact that the minimum bitrate predictor is used for motion vector prediction. Adaptively combining this minimum bitrate prediction scheme with the conventional model-based prediction scheme, more efficient motion vector coding can be achieved. The proposed scheme improves the coding efficiency noticeably for various video sequences.     

Adaptive Correlation Noise Model for DC Coefficients in Wyner‐Ziv Video Coding

An adaptive correlation noise model (CNM) construction algorithm is proposed in this paper to increase the efficiency of parity bits for correcting errors of the side information in transform domain Wyner‐Ziv (WZ) video coding. The proposed algorithm introduces two techniques to improve the accuracy of the CNM. First, it calculates the mean of direct current (DC) coefficients of the original WZ frame at the encoder and uses it to assist the decoder to calculate the CNM parameters. Second, by considering the statistical property of the transform domain correlation noise and the motion characteristic of the frame, the algorithm adaptively models the DC coefficients of the correlation noise with the Gaussian distribution for the low motion frames and the Laplacian distribution for the high motion frames, respectively. With these techniques, the proposed algorithm is able to make a more accurate approximation to the real distribution of the correlation noise at the expense of a very slight increment to the coding complexity. The simulation results show that the proposed algorithm can improve the average peak signal‐to‐noise ratio of the decoded WZ frames by 0.5 dB to 1.5 dB.     

Low delay distributed video coding with refined side information

Distributed video coding (DVC) is a new video coding paradigm based upon two fundamental theoretical results: the Slepian–Wolf and Wyner–Ziv theorems. Among other benefits, this new coding paradigm may allow a flexible complexity allocation between the encoder and the decoder. Several DVC codecs have been developed over the years addressing the specific requirements of emerging applications such as wireless video surveillance and sensor networks. While state-of-the-art DVC codecs, such as the DISCOVER DVC codec, have shown promising RD performance, most DVC codecs in the literature do not consider low delay requirements which are relevant for some of the addressed applications. In this context, the main objective and novelty of this paper is to propose an efficient, low delay and fully practical DVC codec based on the Stanford DVC architecture adopting a side information iterative refinement approach. The obtained performance results show that the developed DVC solution fulfils the objectives regarding relevant benchmarks, notably due to the novel side information creation and correlation noise modeling tools integrated in a side information iterative refinement framework.     

Motion adaptive video coding scheme for time‐varying network

Adaptive video coding algorithms can encode a video stream dynamically on the basis of the amount of bandwidth available in a network. In this paper, a novel approach for adaptive video coding based on look‐up tables has been proposed. On the basis of the network conditions, the proposed codec estimates quantization parameter (QP) and also the spatial resolution for a group of pictures from the look‐up table. Then, QP for each frame is estimated on the basis of the motion content in each frame. More motion leads to more burden of bits while encoding the motion vectors. Also, quantization noise is less prominent in high‐motioned frames than frames possessing low motion information because of the temporal masking phenomenon of the human eyes. So, the main trick of the proposed scheme is to assign higher QP to the frames having higher motion than those having less motion. This method also reduces the requirement of excess bits for encoding of motion vectors having higher motion content. Additionally, QP is adjusted on the basis of the buffer availability in order to avoid bit loss error. Experimental results show the efficacy of the proposed codec. Copyright © 2013 John Wiley & Sons, Ltd.     

Learning-based JNCD prediction for quality-wise perceptual quantization in HEVC

In visual perception, human only perceive discrete-scale quality levels over a wide range of coding bitrate. More clearly, the videos compressed with a series of quantization parameters (QPs) only have limited perceived quality levels. In this paper, perceptual quantization is transformed into the problem of how to determine the just perceived QP for each quality level, and a just noticeable coding distortion (JNCD) based perceptual quantization scheme is proposed. Specifically, multiple visual masking effects are analyzed and a linear regression (LR) based JNCD model is proposed to predict JNCD thresholds for all quality levels at first. According to the JNCD prediction model, the frame-level perceptual QPs for all quality levels are then derived on the premise of that coding distortions are infinitely close to the predicted JNCD thresholds. Based on the predicted frame-level perceptual QPs, the perceived QPs of all quality levels for each coding unit (CU) are finally determined according to a perceptual modulation function. Experimental results show that the proposed quality-wise perceptual quantization scheme is superior to the existing perceptual video coding algorithms significantly, i.e., the proposed perceptual quantization could save more bitrate with better quality.     

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.