Distributed Video Coding Scheme Research Articles

Distributed video coding using interval overlapped arithmetic coding

Distributed video coding (DVC) is a flexible and novel video coding mode that is different from traditional video compression methods, which can shift the complex task such as motion estimation from encoder to decoder. Nowadays, most of the DVC architectures adopt channel coding such as low-density parity-check codes. It is found that arithmetic coding can be also extended to compress correlated sources and even has better performance than the channel coding for short to medium block length sources. Therefore, we propose a DVC scheme using interval overlapped arithmetic coding that is distributed arithmetic coding (DAC) without feedback channel, where the Key frames are compressed using traditional video coder while the Wyner–Ziv frames are compressed using DAC. We compare the rate–distortion performance of the proposed scheme with the state-of-the-arts, and the experimental results indicate that the proposed scheme is competitive. The source code for this scheme is available in GitHub.

Can Gray Code Improve the Performance of Distributed Video Coding?

Gray code application in distributed video coding (DVC) has been studied in the literature and it was claimed that DVC performance could be improved by Gray code because of stronger bitplane correlation presented. However, two factors are ignored in the literature, which renders the aforementioned claim untenable. These factors are log-likelihood ratio (LLR) computation and robustness to wrongly decoded bits, which may influence the DVC performance when different bit representations are used. This paper comprehensively evaluates the performances of Gray code in different DVC schemes, such as feedback channel-based transform domain Wyner–Ziv (FC_TDWZ) video coding, parallel pixel domain Wyner–Ziv video coding, and encoder rate control-based TDWZ (ERC_TDWZ). Experimental results suggest that the Gray code does not always improve the DVC performance, although stronger bitplane correlation is presented. In particular, the performance of FC_TDWZ with Gray code is exactly the same as that with natural bit code, because the same magnitudes of LLRs are obtained. Moreover, the reconstruction quality of the WZ frames in ERC_TDWZ is improved by Gray code not because of stronger bitplane correlation but because Gray code is more robust to wrongly decoded bits induced by rate underestimation. However, these RD gains are quite limited when the rate is controlled accurately at the encoder.

적응적 가중치 기반의 움직임 보상 보간에 기초한 채널 분리형 분산 비디오 부호화기법

Recently, lots of research works have been actively focused on the DVC (Distributed Video Coding) techniques which provide a theoretical basis for the implementation of light video encoder. However, most of these studies have showed poorer performances than the conventional standard video coding schemes such as MPEG-1/2, MPEG-4, H.264 etc. In order to overcome the performance limits of the conventional approaches, several channel-divided distributed video coding schemes have been designed in such a way that some information are obtained while generating side information at decoder side and then these are provided to the encoder side, resulting in channel-divided video coding scheme. In this paper, the interpolation scheme by weighted sum of multiple motion-compensated interpolation frames is introduced and a new channel-divided DVC scheme is designed to effectively describe noisy channels based on the motion vector and its matching characteristics. Through several simulations, it is shown that the proposed method performs better than the conventional methods at low bit-rate and keeps the reconstructed visual quality constantly.

Two-Dimensional Iterative Source-Channel Decoding for Distributed Video Coding

Motivated by the Joint Source-Channel Decoding (JSCD) principle of exploiting the source redundancy, in this treatise we study the application of iterative source-channel decoding (ISCD) conceived for distributed video coding (DVC), where the video signal is modelled by our Iterative Horizontal-Vertical Scanline Model (IHVSM) relying on a first-order Markov process. The IHVSM technique is combined with the classic forward error correction (FEC) codecs employed in the state-of-the-art DVC systems for the sake of reducing the bitrate. Our simulation results show that up to 21.5% bitrate reductions are achieved by employing the proposed ISCD technique in a DVC scheme. Alternatively, a peak signal-to-noise ratio (PSNR) gain of 2.2 dB is achieved at a bitrate of 4.5 Mbps when considering the Foreman sequence.

Distributed video coding with block mode decision to reduce temporal flickering

The common distributed video coding (DVC) systems treat input video frames group by group. In each group of pictures (GOP), usually the first frame, called key frame, is intra-coded and the others are Wyner-Ziv (WZ)-coded. This GOP coding structure presents a fixed and inefficient coding mode switch (key or WZ) at group boundaries, thus preventing a DVC system from adapting the rate-distortion (R-D) performance to varying video content. In this work, a structure of temporal group of blocks (TGOB) with dynamic coding mode (key/WZ) decision is presented. This dynamic TGOB coding architecture determines each image block to be a key block or a WZ block based on spatiotemporal image analysis, resulting in a mode switch of fine granularity in both the spatial and temporal domains. As a consequence, not only the overall coding efficiency is improved, but also the temporal flickering artifacts for the reconstructed video are reduced substantially. Experimental results show that our proposed DVC scheme with block mode decision achieves up to 2.85 dB of quality gain and also up to 51% of temporal flickering reduction, compared to the well-known DISCOVER system.

A New Scheme Based on Pixel-Intense Motion Block Algorithm for Residual Distributed Video Coding

Residual Distributed Video Coding (RDVC) is a branch of the Distributed Video Coding (DVC). By reducing the coding rate, the RDVC scheme gets a better rate-distortion performance. The overall performance of the traditional pixel-based RDVC scheme is better than the traditional transform-based domain DVC scheme. But the traditional RDVC scheme also has some application limitations; for example, the performance of RDVC is bad when it is applied to intense motion regions. And the pixel-based RDVC scheme cannot fully exploit the spatial correlations of the original information. In this paper, we propose a new approach of residual coding combined IMB (intense motion block) extraction algorithm with Low Density Parity Check (LDPC) and Baum-Welch iterative decoding algorithm. Experimental results show that the proposed scheme achieves better rate-distortion performance compared to traditional DVC and RDVC scheme.

Distributed Video Coding Based on Multiple-source Correlation Model

Distributed Video Coding (DVC) is a new video coding paradigm which has the ability to shift coding complexity from encoder to decoder. State-of-art DVC schemes are mainly based on two-source correlation model and only one correlation channel between side information and wyner-ziv frame is considered. In this paper, multiple-source correlation model is introduced into a famous DVC scheme, namely Transform Domain Wyner-Ziv video coder (TDWZ). A soft-input computing algorithm based on multiple-source correlation model is firstly proposed. The correlations a mong multiple side information are separately exploited. Then a new reconstruction function based on multiple source correlation model is also proposed to improve reconstructed image's quality. Experimental results show that the proposed algorithms can effectively improve the coding performance of systems.

Practical distributed video coding in packet lossy channels

Improving error resilience of video communications over packet lossy channels is an important and tough task. We present a framework to optimize the quality of video communications based on distributed video coding (DVC) in practical packet lossy network scenarios. The peculiar characteristics of DVC indeed require a number of adaptations to take full advantage of its intrinsic robustness when dealing with data losses of typical real packet networks. This work proposes a new packetization scheme, an investigation of the best error-correcting codes to use in a noisy environment, a practical rate-allocation mechanism, which minimizes decoder feedback, and an improved side-information generation and reconstruction function. Performance comparisons are presented with respect to a conventional packet video communication using H.264/advanced video coding (AVC). Although currently the H.264/AVC rate-distortion performance in case of no loss is better than state-of-the-art DVC schemes, under practical packet lossy conditions, the proposed techniques provide better performance with respect to an H.264/AVC-based system, especially at high packet loss rates. Thus the error resilience of the proposed DVC scheme is superior to the one provided by H.264/AVC, especially in the case of transmission over packet lossy networks.

움직임 정보 피드백이 가능한 응용을 위한 BER모델을 이용한 고속 분산 비디오 복호화 기법

DVC (Distributed Video Coding) techniques need feedback channel for parity bit control to achieve the good RD performances, however, this causes the DVC system to have high decoding latency. In order to implement in real time environments and to accelerate commercializations, many research works have been focusing on the development of fast video decoding algorithm. As one of the real time implementations, this paper deals with a novel DVC scheme suitable for some application areas where source statistics such as motion information can be provided to the encoder side from the decoder side. That is, this paper propose a fast distributed video decoding scheme to improve the decoding speed by using the feedback of motion information derived in SI generation. Through computer simulations, it is shown that the proposed method outperforms the conventional fast DVC decoding schemes.

패리티 비트 요구량 모델링에 의한 분산 비디오의 고속 복호화 기법

Recently, as one of low complexity video encoding methods, DVC (Distributed Video Coding) scheme has been actively studied. Most of DVC schemes exploit feedback channel to achieve better coding performances, however, this causes these schemes to have high decoding delay. In order to overcome these, this paper proposes a new fast DVC decoding method using parity-bit request model, which can be obtained by using bit-error rate, sent by encoder with motion vector, which is transmitted through feedback channel by decoder after generating side information. Through several simulations, it is shown that the proposed method improves greatly the decoding speed, compared to the conventional schemes.

LDPCA 프레임간 상관성을 이용한 고속 분산 비디오 복호화 기법의 성능 비교

DVC(Distributed Video Coding) techniques have been attracting a lot of research works since these enable us to implement the light-weight video encoder and to provide good coding efficiency by introducing the feedback channel. However, the feedback channel causes the decoder to increase the decoding complexity and requires very high decoding latency because of numerous iterative decoding processes. So, in order to reduce the decoding delay and then to implement in a real-time environment, this paper proposes several parity bit estimation methods which are based on the temporal correlation, spatial correlation and spatio-temporal correlations between LDPCA frames on each bit plane in the consecutive video frames in pixel-domain Wyner-Ziv video coding scheme and then the performances of these methods are compared in fast DVC scheme. Through computer simulations, it is shown that the adaptive spatio-temporal correlation-based estimation method and the temporal correlation-based estimation method outperform others for the video frames with the highly active contents and the low active contents, respectively. By using these results, the proposed estimation schemes will be able to be effectively used in a variety of different applications.

Probabilistic motion-compensated prediction in distributed video coding

Distributed video coding (DVC) constitutes an original coding framework to meet the stringent requirements imposed by uplink-oriented and low-power mobile video applications. The quality of the side information available to the decoder and the efficiency of the employed channel codes are primary factors determining the success of a DVC system. This contribution introduces two novel techniques for probabilistic motion compensation in order to generate side information at the Wyner-Ziv decoder. The employed DVC scheme uses a base layer, serving as a hash to facilitate overlapped block motion estimation at the decoder side. On top of the base layer, a supplementary Wyner-Ziv layer is coded in the DCT domain. Both proposed probabilistic motion compensation techniques are driven by the actual correlation channel statistics and reuse information contained in the hash. Experimental results report significant rate savings caused by the novel side information generation methods compared to previous techniques. Moreover, the compression performance of the presented DVC architecture, featuring the proposed side-information generation techniques, delivers state-of-the-art compression performance.

실제적인 분산 비디오 부호화를 위한 분산 소스 부호화 시스템의 피드백 지연 문제 개선 방안

본 논문에서는 실제적으로 사용 가능한 분산 비디오 부호화 (Distributed Vedio Coding, DVC) 시스템을 구현하기 위하여 기존의 문제였던 높은 피드백 재전송 횟수에 의한 복원 지연문제를 개선하는 방법을 제안한다. 이는 각 압축률 영역에 맞추어 설계된 저밀도 패리티 검사 (Low-Density Parity-Check, LDPC) 부호를 사용함으로써 복원 성능을 높이고 각 부호가 복호에 실패할 경우 다른 부호율의 LDPC 부호를 구성하기 위한 소스 공개 (Source Revealing) 기법을 사용하여 피드백 전송 수를 줄임으로써 문제를 해결한다. 모의 실험 결과, 제안된 방법에 따른 DVC 방법은 기존 방법에 비해 57%의 복호 성능 개선 효과를 얻어 피드백 재전송 횟수를 50% 이상 감소시켰다. Because of the system delay caused by the number of feedback retransmission in Distributed Video Coding (DVC) scheme, it is difficult to realize practical DVC in many cases. In this paper low feedback retransmission Distributed Source Coding (DSC) scheme is proposed for practical DVC scheme based on Low-Density Parity-Check (LDPC) codes because DVC system is an specific application of DSC system. This DSC scheme is achieved by using different LDPC codes optimized in each different compression rate and using source revealing scheme. Optimized LDPC codes provide us much better decoding performance which causes the 57% reduced number of iteration. Consequently, the number of feedback retransmission is decreased by 50%.

Source Modeling for Distributed Video Coding

This paper studies source and correlation models for distributed video coding (DVC). It first considers a two-state HMM, i.e., a Gilbert-Elliott process, to model the bit-planes produced by DVC schemes. A statistical analysis shows that this model allows us to accurately capture the memory present in the video bit-planes. The achievable rate bounds are derived for these ergodic sources, first assuming an additive binary symmetric correlation channel between the two sources. These bounds show that a rate gain can be achieved by exploiting the sources memory with the additive BSC model. A Slepian-Wolf decoding algorithm which jointly estimates the sources and the source model parameters is then described. Simulation results show that the additive correlation model does not always fit well with the correlation between the actual video bit-planes. This has led us to consider a second correlation model (the predictive model). The rate bounds are then derived for the predictive correlation model in the case of memory sources, showing that exploiting the source memory does not bring any rate gain and that the noise statistic is a sufficient statistic for the MAP decoder. We also evaluate the rate loss when the correlation model assumed by the decoder is not matched to the true one. An a posteriori estimation of the correlation channel has hence been added to the decoder in order to use the most appropriate correlation model for each bit-plane. The new decoding algorithm has been integrated in a DVC decoder, leading to a rate saving of up to 10.14% for the same PSNR, with respect to the case where the bit-planes are assumed to be memoryless uniform sources correlated with the SI via an additive channel model.

Transform-domain distributed video coding with rate–distortion-based adaptive quantisation

This study presents a transform-domain distributed video coding (DVC) system with a rate–distortion (R–D)-based Adaptive QuanTisation (AQT) scheme. In the proposed system, the transform-domain Wyner–Ziv frame is divided into partitions and is adaptively quantised based on estimated local R–D characteristics for each partition. The R–D estimation is performed based on a correlation model between the original source information and the side information and can be applied at the decoder without adding complexity to the encoder. Coding results and comparisons with existing DVC schemes and with H.264/AVC interframe and intraframe coding are presented to illustrate the performance of the proposed system.

BLAST-DVC: BitpLAne SelecTive distributed video coding

This paper presents a BitpLAne SelecTive (BLAST) distributed video coding (DVC) system. In the proposed system, the significance of each bitplane is measured at the decoder based on an estimated distortion-rate ratio that makes use of a correlation model for the original source information and the side information. Only the syndrome bits of the bitplanes that have estimated distortion-rate ratios higher than a target distortion-rate ratio, are transmitted and are used to decode the associated bitplanes. The remaining bitplanes are estimated using a minimum-distance symbol reconstruction scheme which makes use of the side information and the LDPCA-decoded bitplanes. Coding results and comparisons with existing DVC schemes and with H.264 intra- and inter-frame coding are presented to illustrate the performance of the proposed system.

Distributed video coding in wireless multimedia sensor network for multimedia broadcasting

Recently the development of Distributed Video Coding (DVC) has provided the promising theory support to realize the infrastructure of Wireless Multimedia Sensor Network (WMSN), which composed of autonomous hardware for capturing and transmission of quality audio-visual content. The implementation of DVC in WMSN can better solve the problem of energy constraint of the sensor nodes due to the benefit of lower computational encoder in DVC. In this paper, a practical DVC scheme, pixel-domain Wyner-Ziv(PDWZ) video coding, with slice structure and adaptive rate selection(ARS) is proposed to solve the certain problems when applying DVC into WMSN. Firstly, the proposed slice structure in PDWZ has extended the feasibility of PDWZ to work with any interleaver size used in Slepian-wolf turbo codec for heterogeneous applications. Meanwhile, based on the slice structure, an adaptive code rate selection has been proposed aiming at reduce the system delay occurred in feedback request. The simulation results clearly showed the enhancement in R-D performance and perceptual quality. It also can be observed that system delay caused by frequent feedback is greatly reduced, which gives a promising support for WMSN with low latency and facilitates the QoS management.

Distributed Video Coding Using JPEG 2000 Coding Scheme

Distributed Video Coding (DVC), based on the theorems proposed by Slepian-Wolf and Wyner-Ziv, is attracting attention as a new paradigm for video compression. Some of the DVC systems use intra-frame compression based on discrete cosine transform (DCT). Unfortunately, conventional DVC systems have low affinity with DCT. In this paper, we propose a wavelet-based DVC scheme that utilizs current JPEG 2000 standard. Accordingly, the scheme has scalability with regard to resolution and quality. In addition, we propose two methods to increase the coding gain of the new DVC scheme. One is the introduction of a Gray code, and the other method involves optimum quantization. An interesting point is that though our proposed method uses Gray code, it still achieves quality scalability. Tests confirmed that the PSNR is increased about 5 [dB] by the two methods, and the PSNR of the new scheme (with methods) is about 1.5--3 [dB] higher than that of conventional JPEG 2000.