A content-aware quantisation mechanism for transform domain distributed video coding

The discrete cosine transform (DCT) is widely applied in modern codecs to remove spatial redundancies, with the resulting DCT coefficients being quantised to achieve compression as well as bit-rate control. In distributed video coding (DVC) architectures like DISCOVER, DCT coefficient quantisation is traditionally performed using predetermined quantisation matrices (QM), which means the compression is heavily dependent on the sequence being coded. This makes bit-rate control challenging, with the situation exacerbated in the coding of high resolution sequences due to QM scarcity and the non-uniform bit-rate gaps between them. This paper introduces a novel content-aware quantisation (CAQ) mechanism to overcome the limitations of existing quantisation methods in transform domain DVC. CAQ creates a frame-specific QM to reduce quantisation errors by analysing the distribution of DCT coefficients. In contrast to the predetermined QM that is applicable to only 4x4 block sizes, CAQ produces QM for larger block sizes to enhance compression at higher resolutions. This provides superior bit-rate control and better output quality by seeking to fully exploit the available bandwidth, which is especially beneficial in bandwidth constrained scenarios. In addition, CAQ generates superior perceptual results by innovatively applying different weightings to the DCT coefficients to reflect the human visual system. Experimental results corroborate that CAQ both quantitatively and qualitatively provides enhanced output quality in bandwidth limited scenarios, by consistently utilising over 90% of available bandwidth

Research and developments of distributed video coding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The recent developed Distributed Video Coding (DVC) is typically suitable for the applications such as wireless/wired video sensor network, mobile camera etc. where the traditional video coding standard is not feasible due to the constrained computation at the encoder. With DVC, the computational burden is moved from encoder to decoder. The compression efficiency is achieved via joint decoding at the decoder. The practical application of DVC is referred to Wyner-Ziv video coding (WZ) where the side information is available at the decoder to perform joint decoding. This join decoding inevitably causes a very complex decoder. In current WZ video coding issues, many of them emphasise how to improve the system coding performance but neglect the huge complexity caused at the decoder. The complexity of the decoder has direct influence to the system output. The beginning period of this research targets to optimise the decoder in pixel domain WZ video coding (PDWZ), while still achieves similar compression performance. More specifically, four issues are raised to optimise the input block size, the side information generation, the side information refinement process and the feedback channel respectively. The transform domain WZ video coding (TDWZ) has distinct superior performance to the normal PDWZ due to the exploitation in spatial direction during the encoding. However, since there is no motion estimation at the encoder in WZ video coding, the temporal correlation is not exploited at all at the encoder in all current WZ video coding issues. In the middle period of this research, the 3D DCT is adopted in the TDWZ to remove redundancy in both spatial and temporal direction thus to provide even higher coding performance. In the next step of this research, the performance of transform domain Distributed Multiview Video Coding (DMVC) is also investigated. Particularly, three types transform domain DMVC frameworks which are transform domain DMVC using TDWZ based 2D DCT, transform domain DMVC using TDWZ based on 3D DCT and transform domain residual DMVC using TDWZ based on 3D DCT are investigated respectively. One of the important applications of WZ coding principle is error-resilience. There have been several attempts to apply WZ error-resilient coding for current video coding standard e.g. H.264/AVC or MEPG 2. The final stage of this research is the design of WZ error-resilient scheme for wavelet based video codec. To balance the trade-off between error resilience ability and bandwidth consumption, the proposed scheme emphasises the protection of the Region of Interest (ROI) area. The efficiency of bandwidth utilisation is achieved by mutual efforts of WZ coding and sacrificing the quality of unimportant area. In summary, this research work contributed to achieves several advances in WZ video coding. First of all, it is targeting to build an efficient PDWZ with optimised decoder. Secondly, it aims to build an advanced TDWZ based on 3D DCT, which then is applied into multiview video coding to realise advanced transform domain DMVC. Finally, it aims to design an efficient error-resilient scheme for wavelet video codec, with which the trade-off between bandwidth consumption and error-resilience can be better balanced

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

High-Quality Symmetric Wyner–Ziv Coding Scheme for Low-Motion Videos

Traditional Wyner-Ziv video coding (WZVC) structures require either intra (Key) or Wyner-Ziv (WZ) coding of frames. Unfortunately, keeping the video quality approximately constant implies drastic bit-rate fluctuations because consecutive frames of different types (Key or WZ) present significantly different compression performances. Moreover, certain scenarios severely limit rate fluctuation. This work proposes a WZVC scheme with low bit-rate fluctuations based on a symmetric coding structure. First, this work investigates the performance of a generic nonasymmetric distributed source coding structure, showing that the low-density parity-check accumulate channel decoding method is best suited. This is used as a basis to design a symmetric WZVC scheme in which every input video frame is divided into four parallel subframes through subsampling, and then the subframes are encoded by using a symmetric method. Compared with the traditional asymmetric WZVC scheme, the proposed scheme can achieve higher bit-rate stability over time, which is a great advantage to guarantee a reliable transmission in many wireless communication application environments in which bit-rate fluctuations are strongly constrained. Simulation results show the effectiveness of the proposed symmetric WZVC scheme in maintaining a steady bit rate and quality, as well as a quality comparison with the traditional WZVC scheme

How to Solve the Fronthaul Traffic Congestion Problem in H-CRAN?

The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as heterogeneous cloud radio access network (H-CRAN) has become a challenging task that requires the most effective utilization of fronthaul network resources. In this paper, we propose and analyze possible solutions to facilitate the fronthaul traffic congestion in the scenario of Coordinated Multi-Point (CoMP) for 5G cellular traffic which is expected to reach ZetaByte by 2017. In particular, we propose to use distributed compression to reduce the fronthaul traffic for H-CRAN. Unlike the conventional approach where each coordinating point quantizes and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user messages are conducted in a joint manner. Our results reveal that, in both dense and ultra-dense urban small cell deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate by more than 50% via joint operation

A simple encoder scheme for distributed residual video coding.

Rate-Distortion (RD) performance of Distributed Video Coding (DVC) is considerably less than that of conventional predictive video coding. In order to reduce the performance gap, many methods and techniques have been proposed to improve the coding efficiency of DVC with increased system complexity, especially techniques employed at the encoder such as encoder mode decisions, optimal quantization, hash methods etc., no doubt increase the complexity of the encoder. However, low complexity encoder is a widely desired feature of DVC. In order to improve the coding efficiency while maintaining low complexity encoder, this paper focuses on Distributed Residual Video Coding (DRVC) architecture and proposes a simple encoder scheme. The main contributions of this paper are as follows: 1) propose a bit plane block based method combined with bit plane re-arrangement to improve the dependency between source and Side Information (SI), and meanwhile, to reduce the amount of data to be channel encoded 2) present a simple iterative dead-zone quantizer with 3 levels in order to adjust quantization from coarse to fine. The simulation results show that the proposed scheme outperforms DISCOVER scheme for low to medium motion video sequences in terms of RD performance, and maintains a low complexity encoder at the same time

REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC

The recently developed Distributed Video Coding (DVC) is typically suitable for the applications where the conventional video coding is not feasible because of its inherent high-complexity encoding. Examples include video surveillance usmg wireless/wired video sensor network and applications using mobile cameras etc. With DVC, the complexity is shifted from the encoder to the decoder. The practical application of DVC is referred to as Wyner-Ziv video coding (WZ) where an estimate of the original frame called "side information" is generated using motion compensation at the decoder. The compression is achieved by sending only that extra information that is needed to correct this estimation. An error-correcting code is used with the assumption that the estimate is a noisy version of the original frame and the rate needed is certain amount of the parity bits. The side information is assumed to have become available at the decoder through a virtual channel. Due to the limitation of compensation method, the predicted frame, or the side information, is expected to have varying degrees of success. These limitations stem from locationspecific non-stationary estimation noise. In order to avoid these, the conventional video coders, like MPEG, make use of frame partitioning to allocate optimum coder for each partition and hence achieve better rate-distortion performance. The same, however, has not been used in DVC as it increases the encoder complexity. This work proposes partitioning the considered frame into many coding units (region) where each unit is encoded differently. This partitioning is, however, done at the decoder while generating the side-information and the region map is sent over to encoder at very little rate penalty. The partitioning allows allocation of appropriate DVC coding parameters (virtual channel, rate, and quantizer) to each region. The resulting regions map is compressed by employing quadtree algorithm and communicated to the encoder via the feedback channel. The rate control in DVC is performed by channel coding techniques (turbo codes, LDPC, etc.). The performance of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and an adaptive WZ DVC is designed both in transform domain and in pixel domain. The transform domain WZ video coding (TDWZ) has distinct superior performance as compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the ' spatial redundancy during the encoding. The performance evaluations show that the proposed system is superior to the existing distributed video coding solutions. Although the, proposed system requires extra bits representing the "regions map" to be transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art frame based DVC by 0.6-1.9 dB. The feedback channel (FC) has the role to adapt the bit rate to the changing ' statistics between the side infonmation and the frame to be encoded. In the unidirectional scenario, the encoder must perform the rate control. To correctly estimate the rate, the encoder must calculate typical side information. However, the rate cannot be exactly calculated at the encoder, instead it can only be estimated. This work also prbposes a feedback-free region-based adaptive DVC solution in pixel domain based on machine learning approach to estimate the side information. Although the performance evaluations show rate-penalty but it is acceptable considering the simplicity of the proposed algorithm. vii