Robust Video Transmission Research Articles

Design of Robust Video Transmission System by Using Efficient Forward Error Correction Scheme

The advent of modern digital technologies has made multimedia communication systems one of the most demanding technologies of the time. The use of available bandwidth for efficient and errorless multimedia communication is the key challenge for the wireless communication research community. However, a wireless network has the disadvantage of being prone to random channel noise and data contamination. This paper proposes a robust video transmission framework by using an efficient forward error correction technique. In this work, the experimental performance of widely used forward error correction codes i.e., Convolution codes, LDPC codes, Turbo codes, and Concatenated codes, are compared based on their capability to compensate the channel noise and distortion. An efficient encoding scheme is devised for the transmission of YUV encoded frames by using the selected FEC codes in a noisy channel environment. The retrieved video is analysed by using the Peak Signal-to-Noise ratio and bit error rate as performance metrics. The results and cross comparison shows that concatenated codes have a handsome improvement in avoiding channel contamination and distortion.

An Adaptive Fuzzy based FEC Algorithm for Robust Video Transmission over Wireless Networks

Forward Error Correction (FEC) is a commonly adopted mechanism to mitigate packet loss/bit error during real-time communication. An adaptive, Fuzzy based FEC algorithm to provide a robust video quality metric for multimedia transmission over wireless networks has been proposed to optimize the redundancy of the generated code words from a Reed-Solomon encoder and to save the bandwidth of the network channel. The scheme is based on probability estimations derived from the data loss rates related to the recovery mechanism at the client end. By applying the adaptive FEC, the server uses the reports to predict the next network loss rate using a curve-fitting technique to generate the optimized number of redundant packets to meet specific residual error rates at the client end. Simulation results in the cellular system show that the video quality is massively adapted to the optimized FEC codes based on the probability of packet loss and packet correlation in a wireless environment.

LensCast: Robust Wireless Video Transmission Over MmWave MIMO With Lens Antenna Array

In this paper, we present LensCast, a novel cross-layer video transmission framework for wireless networks, which seamlessly integrates millimeter wave (mmWave) lens multiple-input multiple-output (MIMO) with robust video transmission. LensCast is designed to exploit the video content diversity at the application layer, together with the spatial path diversity of lens antenna array at the physical layer, to achieve graceful video transmission performance under varying channel conditions. In LensCast, a transmission distortion minimization problem is formulated with the consideration of video chunk scheduling, path matching and power allocation, which is an intractable mixed integer non-linear programming (MINLP) problem. The solution of this MINLP problem is converted into resource allocation (i.e., joint path matching and power allocation) plus chunk scheduling. First, resource allocation is investigated with given chunk scheduling results. By analyzing the optimality of the resource allocation problem, a winner-takes-all assignment is obtained to guide resource allocation. After that, a greedy water-filling algorithm is proposed as a near-optimal solution. Second, we propose a low-complexity chunk scheduling algorithm to schedule chunks for each transmission. Simulation results demonstrate that the proposed LensCast achieves an improved performance in terms of both peak signal-to-noise ratio and visual quality comparing with reference schemes.

Robust Video Broadcast for Users With Heterogeneous Resolution in Mobile Networks

Recently, robust video transmission system that can eliminate the cliff effect in digital video transmission has attracted great interest from both academia and industry. By linearizing the whole system, robust video transmission is intrinsically scalable to channel conditions in mobile networks. However, the heterogeneity of user devices in terms of viewing resolution has not been well studied for robust video broadcast systems. In this paper, we propose a spatial scalability enabled robust video broadcast (SSRVB) system, aiming at accommodating diverse users with both heterogeneous resolutions and heterogeneous channel conditions. In SSRVB, a novel spatial decomposition method based on linear projection is first designed for robust video transmission. Then the transmission distortion minimization problem with joint subcarrier matching and power allocation is formulated. A near-optimal low-complexity subcarrier matching algorithm based on auction theory and an optimal power allocation strategy are also proposed. Furthermore, an iterative algorithm is designed to solve the problem of joint resource allocation. Simulation results demonstrate that SSRVB can achieve an average of 3 dB gain when compared with the reference schemes (i.e., ECast, MCast, discrete wavelet transform (DWT) based scheme, and scalable video coding (SVC) scheme) in terms of average peak signal-to-noise ratio under heterogeneous scenarios.

Reliable and Robust Unmanned Aerial Vehicle Wireless Video Transmission

The wireless video transmission environment of unmanned aerial vehicles (UAVs) is complex and unstable given the high mobility and changeable working conditions of UAVs, which lead to burst and consecutive errors and high error rates. A compressed video stream is extremely sensitive to transmission errors, such that even a single bit error sharply degrades the video quality. Hence, we propose an intraframe pixel-row-interleaved error concealment algorithm that interleaves pixel rows to generate high similarity in different parts of a frame, thereby achieving intraframe error resilience. Subsequently, we suggest an interframe time-field-interleaved alternative motion-compensated prediction that allows for automatic error elimination and recovers at least four consecutive frames in wireless video communications. The experiments demonstrate that the proposed algorithms recover frames with excellent subjective and objective effects. Moreover, these algorithms can provide reliable and robust video transmission for UAVs.

MuVi: Multiview Video Aware Transmission Over MIMO Wireless Systems

Multiview video is essential for various mobile three-dimensional (3D) and immersive applications that can capture scenes from multiple angles for better user experience. However, robust transmission of multiview video is very challenging in wireless networks due to high bandwidth requirement and time-varying channel quality. Though the up-to-date 802.11 system enables spatial multiplexing MIMO to enhance transmission capacity, it is still agnostic to 3D source coding structure in the transmission. In this paper, we study the optimal resource allocation problem in MIMO systems that deliver 3D content with multiview video coding. The basic idea is to exploit the channel diversity of multiple antennas and the source coding characteristics so as to achieve unequal error protection against channel errors. To achieve this goal, we develop a nonlinear mixed integer programming framework to perform antenna selection and power allocation, and propose low-complexity algorithms to assign these resources. We implement a proof-of-concept system, namely MuVi, on the software-defined-radio platform, WARP, to evaluate the proposed algorithms. MuVi is the practical system to tackle 3D multiview streaming in the latest Wi-Fi networks such as IEEE 802.11ac under realistic channel conditions. Extensive experimental results demonstrate that the peak signal-to-noise-ratio of MuVi significantly outperforms that of the conventional power allocation scheme in a variety of indoor environments.

Adaptive Hybrid Digital–Analog Video Transmission in Wireless Fading Channel

We propose an adaptive hybrid digital–analog video transmission (A-HDAVT) scheme for robust video streaming in mobile networks with realistic fading channels. This scheme is fundamentally different from recent research in hybrid digital–analog video transmission in which wireless channels are unrealistically assumed to be Gaussian. For fading channels, it is critical to take full advantage of diversity in both video contents and multiuser channels. Like all hybrid approaches, A-HDAVT is designed to exploit the benefits from both digital and analog systems. To achieve this goal, each group of pictures is first transformed into one low-pass frame and several high-pass frames with motion-compensated temporal filtering. The critical low-pass frame is reliably transmitted as base layer in a digital mode, while high-pass frames are transmitted as enhancement layers in an analog mode to achieve desired graceful degradation performance. In analog transmission, we introduce a channel prediction-based adaptive power-distortion optimization (P-APDO) scheme to combat channel fading in mobile networks. The basic idea behind P-APDO is to perform power allocation based on the video content as well as the predicted channel status. Furthermore, we also investigate the multiuser scenarios in which the content diversity and channel diversity among users are appropriately exploited. Extensive simulations have been carried out to evaluate the performance of A-HDAVT under various degrees of channel fading. The results show that A-HDAVT achieves significant performance gains over competing schemes Robust Uncoded Video Transmission, Parcast, and Softcast in both single-user and multiuser scenarios.

Multiple description video coding based on adaptive data reuse

In this paper, an efficient multiple description coding (MDC) method, called the adaptive data reuse MDC (ADR-MDC), is proposed for robust video transmission. The proposed ADR-MDC first groups four sub-sequences, which are generated by performing spatial down-sample operation on each frame of input video sequence, into two descriptions. In each description, one sub-sequence is directly encoded and decoded by applying the H.264/AVC encoder and decoder, while the other is encoded and decoded at each macroblock (MB) based on the adaptive data reuse criterion, which are developed by making full use of the spatial and temporal correlations among the sub-sequences. Experimental results have shown that the proposed ADR-MDC scheme possesses higher error resilient ability and obtains better reconstructed video than the existing state-of-the-art MDC method.

Layered multiple description video coding using dual-tree discrete wavelet transform and H.264/AVC

A novel hybrid layered multiple description video coding (HLMDVC) algorithm is proposed to provide a robust and flexible video transmission via unreliable networks, like Internet or the wireless ne...

Joint Redundant and Random Network Coding for Robust Video Transmission over Lossy Networks

In this paper a novel unequal packet loss protection scheme R2NC based on low-triangular global coding matrix with ladder-shaped partition is presented, which combines redundant and random network coding for robust H.264/SVC video transmission. Firstly, the error-correcting capabilities of redundant network coding make our scheme resilient to loss. Secondly, the implementation of random network coding at the intermediate nodes with multiple input links can reduce the cost of network bandwidth, thus reducing the end-to-end delay for video transmission. Thirdly, the low-triangular global coding matrix with ladder-shaped partition is maintained throughout the R2NC processes to reduce the impact of global coding matrix's rank deficiency on video transmission and provide unequal erasure protection for H.264/SVC priority layers. The redundant network coding avoids the retransmission of lost packets and improves error-correcting capabilities of lost packets. Based only on the knowledge of the packet loss rates on the output links, the source node and intermediate nodes can make decisions for redundant network coding and random network coding (i.e., how much redundancy to add at this node). However, the redundancy caused by redundant network coding makes the network load increases. In order to improve network throughput, we performed random network coding at the intermediate nodes. Our approach is grounded on the overall distortion of reconstructed video minimization by optimizing the amount of redundancy assigned to each layer. The convex optimization model is constructed under the constraint of network coding and scalable video coding. Experimental results are shown to demonstrate the significant improvement of H.264/SVC video reconstruction quality with R2NC over packet lossy networks.

Two-description distributed video coding for robust transmission

In this article, a two-description distributed video coding (2D-DVC) is proposed to address the robust video transmission of low-power capturers. The odd/even frame-splitting partitions a video into two sub-sequences to produce two descriptions. Each description consists of two parts, where part 1 is a zero-motion based H.264-coded bitstream of a sub-sequence and part 2 is a Wyner-Ziv (WZ)-coded bitstream of the other sub-sequence. As the redundant part, the WZ-coded bitstream guarantees that the lost sub-sequence is recovered when one description is lost. On the other hand, the redundancy degrades the rate-distortion performance as no loss occurs. A residual 2D-DVC is employed to further improve the rate-distortion performance, where the difference of two sub-sequences is WZ encoded to generate part 2 in each description. Furthermore, an optimization method is applied to control an appropriate amount of redundancy and therefore facilitate the tuning of central/side distortion tradeoff. The experimental results show that the proposed schemes achieve better performance than the referenced one especially for low-motion videos. Moreover, our schemes still maintain low-complexity encoding property.

Hierarchical B-picture mode decision in H.264/SVC

To enable robust video transmission over heterogeneous networks, the hierarchical B-picture prediction structure is employed in the state-of-the-art video coding standard H.264/SVC, aiming to produce scalable bitstreams with various frame rates. However, the exhaustive mode decision process with the hierarchical B-picture structure increases the computational complexity of H.264/SVC encoding dramatically. In this paper, a fast mode decision algorithm is proposed to speed up H.264/SVC encoding with the hierarchical B-picture structure, which is achieved by utilizing macroblock (MB) features, correlation of temporal–spatial neighboring MBs, and the discrepant characteristics of hierarchical layers. Extensive experimental results demonstrate that the proposed algorithm is able to reduce the encoding time of H.264/SVC significantly for video sequences with a wide range of resolutions, and meanwhile the video quality and compression ratio are well preserved.

Reversible Data Hiding-Based Approach for Intra-Frame Error Concealment in H.264/AVC

Error concealment plays an important role in robust video transmission. Recently, Chen and Leung presented an efficient data hiding-based (DH-based) approach to recover corrupted macroblocks from the intra-frame of an H.264/AVC sequence, but it suffers from the quality degradation problem. Since the quantized discrete cosine transform coefficients of an H.264/AVC sequence tend to form a Laplace distribution, we therefore propose a reversible DH-based approach for intra-frame error concealment based on this characteristic. Our design is able to achieve no quality degradation. Experimental results demonstrate that the quality of recovered video sequences obtained by our approach is indeed superior to that of the DH-based method. In addition, the quality advantage of our approach is illustrated when compared with the previous five related methods.

Random linear network coding with ladder-shaped global coding matrix for robust video transmission

Robust video multicast in erasure networks using network coding (NC) to reduce the impact of packet loss is studied in this paper. In our proposed solution, random linear network coding (RLNC) is adopted at intermediate nodes of the network. RLNC linearly combines a group of packets by randomly selecting weighting coefficients on a finite field, and the loss of an RLNC-coded packet is equivalent to the loss of one constraint in a linear system of equations required for RLNC decoding. Unless the global coding coefficient matrix, or simply called the global coding matrix (GCM), is of full rank, a receive node cannot reconstruct all source packets. To address this rank deficiency problem, we propose to construct a special-structured GCM, called the ladder-shaped GCM (LGCM), for layered H.264/SVC (scalable video coding) video multicast. The ladder shape of the sparse coding matrix is maintained throughout the RLNC process to achieve two objectives: (1) to enable partial decoding of a block; and (2) to provide unequal erasure protection for H.264/SVC priority layers. Furthermore, quality degradation is minimized by optimizing the amount of redundancy assigned to each layer, and graceful quality degradation is achieved by error concealment (EC). Simulation results are given to demonstrate the superior performance of the proposed RLNC–LGCM scheme over the traditional RLNC with a generalGCM.

Robust Video Coding Based on Multiple Description Scalar Quantization With Side Information

This paper addresses the problem of video compression for robust transmission on lossy Internet networks. The approach developed relies on multiple description coding (MDC) principles. Predictive multiple description video coding has already been considered for robust video transmission over lossy channels. However, MDC, when combined with motion-compensated prediction, is known to suffer from predictive mismatch: in presence of losses, the prediction signal available at the decoder may differ from the one used at the encoder. In this paper, we describe a video compression scheme based on MDC and Wyner-Ziv (WZ) coding. The input sequence is structured into groups of pictures which contain one key frame and one WZ frame. Each frame is first transformed with a wavelet transform and the resulting frequency bands are quantized with a multiple description scalar quantizer. Two balanced descriptions of the video input are thus generated. The quantization indexes of the WZ frames are coded with an low-density parity-check accumulate-based Slepian-Wolf (SW) coder. The lateral receivers first decode the received key frame lateral descriptions, and then construct the side information needed for decoding the corresponding WZ frame descriptions by motion-compensated interpolation. In the case where the two WZ data descriptions are received, the central decoder can perform a separate SW decoding of the two sequences of quantization indexes. A joint iterative decoding approach of the two WZ descriptions is also described which improve the central WZ data decoding performance, however, at the expense of increased decoding complexity. The influence of the proposed iterative decoding technique and of the amount of redundancy on the lateral and central rate-distortion performance of the algorithm is studied.

A Robust and Flexible Unbalanced Multiple Description Video Coding and Transmission Scheme

This paper propose a flexible and robust unbalanced multiple description coding and transmission scheme,which is capable of quickly recovering from packet losses and ensuring continuous playback,and further adaptive to both multiple path and single path transmission.Furthermore,this paper discusses the problem of rate allocation between different descriptions when only single path transmission is available and proposes an approximate while efficient rate allocation scheme with the help of two-state Markov link model and a representative rate-distortion model.The experimental results demonstrate the effectiveness of the proposed scheme.

Improved Resilience for Video Over Packet Loss Networks With MDC and Optimized Packetization

We investigate the problem of robust video transmission over lossy packet networks. A resilient video coding framework is important to ensure quality video over these networks. We propose a combination of a rate-distortion optimized multiple description codec and an integrated packetization method to constitute the error resilient codec. Multiple description (MD) coding techniques utilize path-diversity (multiple paths between sender and receiver) in networks by sending the descriptions along different paths. Two different optimization controls for the MD codec are proposed that are suited to variable rates of packet loss for multipath transmission of the MD coded video. An optimized strategy for packetizing the descriptions is also proposed which guarantees that each packet is self-contained and efficient. Simulations done under various packet loss scenarios show the need for two different optimization strategies and also that the developed MD codec achieves significantly improved video quality when compared with similar techniques.

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.

Multiple description video coding based on residuum compensation

As one of the focus areas of robust video coding and transmission, multiple description video coding has attracted comprehensive attention. The low coding efficiency of multiple description video coding is always the major challenge in this field. In order to improve the performance of multiple description video coding, this paper proposes a scheme based on residuum compensation. In this scheme, each original video frame is encoded with a traditional encoder first to get the first description. Then the error residuum of each coded frame is added up to the corresponding original frame and the resulting compensated frame is encoded by another traditional encoder to generate the second description successively. This work uses JM10.0 of H.264/AVC as video coding codec to conduct the experiments. The experimental results show that the proposed scheme has good coding performance. Compared to state of art traditional single description encoder, the efficiency can be as high as 90%, i.e. the redundancy is only 10% to 20%.

A low-complexity rate allocation algorithm for joint source-channel video coding

The problem of enabling robust video transmission over lossy networks has become increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks. The more the coding process relies on an intensive use of prediction to improve the coding gain, the more the reconstructed sequence proves to be sensitive to information losses. As a matter of fact, it is necessary to introduce some redundant data in order to increase the robustness of the coded bit stream. A possible solution can be found filling a matrix structure with RTP packets and applying a Forward Error Correction (FEC) code on its rows. However, the matrix size and the chosen FEC code affect the performance of the coding system. The paper proposes a novel adaptation technique that tunes the amount of redundant information included in the packet stream and differs from previously proposed solutions since it relies on the percentage of null quantized transform coefficients in place of the activity or the Mean Square Error (MSE). This strategy is then integrated in a joint source-channel coder rate allocation algorithm that shares the available bits between the H.264/AVC coder and the channel coder according to the significance of the frame in the decoding process. Experimental results show that the presented approach significantly improves the quality of the reconstructed sequences at the decoder with respect to activity-based strategies and requires a low computational complexity.