Error-resilient performance of Dirac video codec over packet-erasure channel

Video transmission over the wireless or wired network requires error-resilient mechanism since compressed video bitstreams are sensitive to transmission errors because of the use of predictive coding and variable length coding. This paper investigates the performance of a simple and low complexity error-resilient coding scheme which combines source and channel coding to protect compressed bitstream of wavelet-based Dirac video codec in the packet-erasure channel. By partitioning the wavelet transform coefficients of the motion-compensated residual frame into groups and independently processing each group using arithmetic and Forward Error Correction (FEC) coding, Dirac could achieves the robustness to transmission errors by giving the video quality which is gracefully decreasing over a range of packet loss rates up to 30% when compared with conventional FEC only methods. Simulation results also show that the proposed scheme using multiple partitions can achieve up to 10 dB PSNR gain over its existing un-partitioned format. This paper also investigates the error-resilient performance of the proposed scheme in comparison with H.264 over packet-erasure channel

Channel coding for progressive images in a 2-D time-frequency OFDM block with channel estimation errors.

Coding and diversity are very effective techniques for improving transmission reliability in a mobile wireless environment. The use of diversity is particularly important for multimedia communications over fading channels. In this work, we study the transmission of progressive image bitstreams using channel coding in a 2-D time-frequency resource block in an OFDM network, employing time and frequency diversities simultaneously. In particular, in the frequency domain, based on the order of diversity and the correlation of individual subcarriers, we construct symmetric n -channel FEC-based multiple descriptions using channel erasure codes combined with embedded image coding. In the time domain, a concatenation of RCPC codes and CRC codes is employed to protect individual descriptions. We consider the physical channel conditions arising from various coherence bandwidths and coherence times, leading to a range of orders of diversities available in the time and frequency domains. We investigate the effects of different error patterns on the delivered image quality due to various fade rates. We also study the tradeoffs and compare the relative effectiveness associated with the use of erasure codes in the frequency domain and convolutional codes in the time domain under different physical environments. Both the effects of intercarrier interference and channel estimation errors are included in our study. Specifically, the effects of channel estimation errors, frequency selectivity and the rate of the channel variations are taken into consideration for the construction of the 2-D time-frequency block. We provide results showing the gain that the proposed model achieves compared to a system without temporal coding. In one example, for a system experiencing flat fading, low Doppler, and imperfect CSI, we find that the increase in PSNR compared to a system without time diversity is as much as 9.4 dB

Application layer systematic network coding for sliced H.264/AVC video streaming

Application Layer Forward Error Correction (AL-FEC) with rateless codes can be applied to protect the video data over lossy channels. Expanding Window Random Linear Codes (EW RLCs) are a flexible unequal error protection fountain coding scheme which can provide prioritized data transmission. In this paper, we propose a system that exploits systematic EW RLC for H.264/Advanced Video Coding (AVC) slice-partitioned data. The system prioritizes slices based on their PSNR contribution to reconstruction as well as temporal significance. Simulation results demonstrate usefulness of using relative slice priority with systematic codes for multimedia broadcast applications

Channel Coding for Progressive Images in a 2-D Time-Frequency OFDM Block With Channel Estimation Errors

Coding and diversity are very effective techniques for improving transmission reliability in a mobile wireless environ- ment. The use of diversity is particularly important for multimedia communications over fading channels. In this work, we study the transmission of progressive image bitstreams using channel coding in a 2-D time-frequency resource block in an OFDM network, em- ploying time and frequency diversities simultaneously. In partic- ular, in the frequency domain, based on the order of diversity and the correlation of individual subcarriers, we construct symmetric -channel FEC-based multiple descriptions using channel erasure codes combined with embedded image coding. In the time domain, a concatenation of RCPC codes and CRC codes is employed to pro- tect individual descriptions. We consider the physical channel con- ditions arising from various coherence bandwidths and coherence times, leading to a range of orders of diversities available in the time and frequency domains. We investigate the effects of different error patterns on the delivered image quality due to various fade rates. We also study the tradeoffs and compare the relative effec- tiveness associated with the use of erasure codes in the frequency domain and convolutional codes in the time domain under different physical environments. Both the effects of intercarrier interference and channel estimation errors are included in our study. Specifi- cally, the effects of channel estimation errors, frequency selectivity and the rate of the channel variations are taken into consideration for the construction of the 2-D time-frequency block. We provide results showing the gain that the proposed model achieves com- pared to a system without temporal coding. In one example, for a system experiencing flat fading, low Doppler, and imperfect CSI, we find that the increase in PSNR compared to a system without time diversity is as much as 9.4 dB

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

Optimized cross-layer forward error correction coding for H.264 AVC video transmission over wireless channels

Forward error correction (FEC) codes that can provide unequal error protection (UEP) have been used recently for video transmission over wireless channels. These video transmission schemes may also benefit from the use of FEC codes both at the application layer (AL) and the physical layer (PL). However, the interaction and optimal setup of UEP FEC codes at the AL and the PL have not been previously investigated. In this paper, we study the cross-layer design of FEC codes at both layers for H.264 video transmission over wireless channels. In our scheme, UEP Luby transform codes are employed at the AL and rate-compatible punctured convolutional codes at the PL. In the proposed scheme, video slices are first prioritized based on their contribution to video quality. Next, we investigate the four combinations of cross-layer FEC schemes at both layers and concurrently optimize their parameters to minimize the video distortion and maximize the peak signal-to-noise ratio. We evaluate the performance of these schemes on four test H.264 video streams and show the superiority of optimized cross-layer FEC design.Peer reviewedElectrical and Computer Engineerin

Adaptive Prioritized Random Linear Coding and Scheduling for Layered Data Delivery From Multiple Servers

In this paper, we deal with the problem of jointly determining the optimal coding strategy and the scheduling decisions when receivers obtain layered data from multiple servers. The layered data is encoded by means of prioritized random linear coding (PRLC) in order to be resilient to channel loss while respecting the unequal levels of importance in the data, and data blocks are transmitted simultaneously in order to reduce decoding delays and improve the delivery performance. We formulate the optimal coding and scheduling decisions problem in our novel framework with the help of Markov decision processes (MDP), which are effective tools for modeling adapting streaming systems. Reinforcement learning approaches are then proposed to derive reduced computational complexity solutions to the adaptive coding and scheduling problems. The novel reinforcement learning approaches and the MDP solution are examined in an illustrative example for scalable video transmission . Our methods offer large performance gains over competing methods that deliver the data blocks sequentially. The experimental evaluation also shows that our novel algorithms offer continuous playback and guarantee small quality variations which is not the case for baseline solutions. Finally, our work highlights the advantages of reinforcement learning algorithms to forecast the temporal evolution of data demands and to decide the optimal coding and scheduling decisions