Multiple Description Coding Research Articles

Multiple description image coding using Schur transform

A novel obvious and robust image Multiple Description Coding (MDC) using Schur transform (ST)is presented in this work. To overcome the inherent drawbacks in the discrete wavelet transform (DWT)which are the hardware implementation and computational complexityIn the MDC approach, two or more correlated descriptions of the same data aregenerated, which can be independently decoded, and yield mutually refinable information. Therefore, the quality of the recovered signal is dependent only on the number of received descriptions, and not on the specific loss pattern. The new techniquewas analyzed and compared to the conventional approach in the case of four descriptions by using multiple grayscale test images having different spectral characteristics.Theexperimental results of Schur transform (ST) compared to discrete wavelet transform (DWT)show that our method achievesbetter performance in terms of delivered peaksignal to noise ratio (PSNR) and visual image quality reconstruction.The proposed MDC has a low redundancy and outperforms the conventionalscheme for image transmission over error-prone networks.Therefore, the proposed approach provides an easier practical implementation and a better redundancy performancethan the classical approach.

Multiple Description Coding for Best-Effort Delivery of Light Field Video Using GNN-Based Compression

In recent years, Light Field (LF) video has grabbed much attention as an emerging form of immersive media. LF collects, through a lens matrix, light information emanating in every direction, and obtains rich information about the scene, providing users with an immersive 6 Degrees of Freedom (DoF) experience. The visual content between different viewpoints is highly homogenized, suggesting the possibility of good compression and encoding. However, most fixed-structure LF coding schemes are difficult to adapt to the real-time requirements of different LF applications and best-effort network conditions causing packet loss. In this paper, we propose a dynamic adaptive LF video transmission scheme that can achieve high compression and yet provide near-distortion-free LF video when the network condition is stable. Additionally, for unstable network conditions a description scheduling algorithm is proposed, which can decode the LF video with the highest possible quality even if partial data cannot be received completely and/or timely. We achieve this by designing a Multiple Description Coding (MDC) based solution to transport the LF video compressed by a Graph Neural Network (GNN) model. Experimental results show that the scheduling algorithm can improve the quality of the decoding results by 3% to 15%. Compared with other similar schemes, our system greatly improves the reliability of the video streaming system against packet loss/error and supports heterogeneous receivers.

HEVC Compatible Multiple Description Coding for Robust Video Transmission over Lossy Networks

In this paper, we propose a novel multiple description coding (MDC) method, which offers benefits of the new H.265/HEVC video coding standard combined with path diversity systems for robust video transmissions. In the proposed method, two descriptions including odd and even video subsequences are encoded using H.265/HEVC coder and then transmitted over two distinct channels of a path diversity system. At the receiver, the proposed MDC decoder is designed using a novel concept of distributed video coding (DVC) to provide a high image quality for the reconstructed description. Experimental results show that the proposed method can achieve a wide range of tradeoffs between coding efficiency and error resilience, and provide much better H.265/HEVC quality of experiences (QoEs) for users than other conventional MDC methods results

STBC-Assisted MDC-NOMA Image Transmission Scheme for Multi-Antenna Systems

As an efficient and interference-resistant coding technique, multiple description coding (MDC) is proposed with the aim to solve the transmission unreliability problem caused by packet errors, loss or blocking delays. The integration of MDC with non-orthogonal multiple access (NOMA) scheme (MDC-NOMA) can effectively boost the robustness and throughput of the underlying system. Additionally, space-time block coding (STBC) can further enhance the system reliability with increased diversity gain, as well as reduced decoding complexity. In this paper, we propose a novel framework referred to as MDC-NOMA-STBC, in which we apply Alamouti STBC integrated with MDC and NOMA to implement more reliable transmission. Specifically, NOMA signals are constructed by superimposing the descriptions from different users, then transmitted by the base station (BS) using Alamouti STBC. In order to substantiate the performance of the proposed framework, first, we derive closed-form expressions of both the outage probability and ergodic rate for each user in a two-antenna BS scenario. Second, for multi-antenna BS, we investigate different antenna selection strategies to further enhance the outage performance under the considered framework, whose analytical expression is provided wherever possible. Third, Monte Carlo simulation results are presented to validate our theoretical framework and to corroborate the superiority of the proposed MDC-NOMA-STBC over state-of-the-art MDC-NOMA scheme. Moreover, under realistic contexts with image transmission, it is confirmed that MDC-NOMA-STBC outperforms its counterpart MDC-NOMA in terms of the peak signal-to-noise ratio and the bit error rate.

Spatial-frequency HEVC multiple description video coding with adaptive perceptual redundancy allocation

Multiple description coding (MDC) approaches improve the error-resilient performance of video transmission by introducing redundancy. The existing multiple description video coding (MDVC) schemes are rarely designed for particular coding structure of HEVC, and the characteristics of the human visual system (HVS) are seldom considered. In this paper, a spatial-frequency multiple description video coding with adaptive perceptual redundancy allocation framework, named SF-PMDVC, is proposed for HEVC. For descriptions generation, after polyphase down-sampling in spatial domain, a transformation based on integer discrete cosine transform (DCT) is expended to adapt to the flexible coding unit partitioning process in HEVC, and the frequency coefficients are segmented and mapped to reduce the bitrate of each description. To further improve the performance of MDVC, an adaptive perceptual redundancy allocation strategy based on visual saliency is proposed, which improves the coding efficiency adapting to the visual perception. Experimental results show that the proposed scheme improves the error resiliency of HEVC by achieving superior objective and subjective reconstructed video quality as compared to the state-of-the-art MDVC methods for HEVC.

Repair Rates for Multiple Descriptions on Distributed Storage

In a traditional distributed storage system, a source can be restored perfectly when a certain subset of servers is contacted. The coding is independent of the contents of the source. This paper considers instead a lossy source coding version of this problem where the more servers that are contacted, the higher the quality of the restored source. An example could be video stored on distributed storage. In information theory, this is called the multiple description problem, where the distortion depends on the number of descriptions received. The problem considered in this paper is how to restore the system operation when one of the servers fail and a new server replaces it, that is, repair. The requirement is that the distortions in the restored system should be no more than in the original system. The question is how many extra bits are needed for repair. We find an achievable rate and show that this is optimal in certain cases. One conclusion is that it is necessary to design the multiple description codes with repair in mind; just using an existing multiple description code results in unnecessary high repair rates.

Multiple Description Coding for Enhancing Outage and Video Performance Over Relay-Assisted Cognitive Radio Networks

Multimedia content delivery, such as video transmission over wireless networks, imposes significant challenges include spectrum capacity and packet losses. The cognitive radio (CR) technology is developed to solve the spectrum issue, while multiple description coding (MDC) is one of the promising source coding techniques to alleviate packet loss problems and exploit the benefit of path diversity. The source information was split into several descriptions in MDC, then transmitted over a network with multiple paths. The quality of the received data increases with the number of descriptions received at the receiver. In this paper, the proposed system comprises of relay-assisted cognitive radio network using the MDC technique for video transmission. In the simulations, the outage performance of the MDC scheme over two networks, which were relay-assisted network and non-relay network, were compared. Then, the outage probability was used to estimate the video quality, peak signal to noise ratio (PSNR) of the received video. The results obtained show the benefits of the relay assisted networks by 9% improvement on average outage performance over the non-relay network. Furthermore, the video performance improved by an average of 9% in PSNR compared to the non-relay system.

Error-resilient coding by convolutional neural networks for underwater video transmission

Due to an increased number of transmission errors, the real-time transmission needs for seafloor videos are imposing severe challenges on underwater acoustic networks. In this work, we propose an error-resilient coding method based on convolutional neural networks and multiple descriptions to combat packet losses for underwater video transmission. By exploiting the inter-frame motion information, our convolutional neural networks propagate the regions of interest, providing extra protection for multiple description coding. To achieve a good tradeoff between coding efficiency and error resiliency, video sequences are split into two kinds of descriptions that are encoded under a bit-rate constraint condition. Simulation experiments with underwater video datasets are conducted to verify the effectiveness of our approach at different packet loss rates, compared to state-of-the-art video coding schemes.

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

Network coding (NC) is considered a breakthrough to improve throughput, robustness, and security of wireless networks. Although the theoretical aspects of NC have been extensively investigated, there have been only few experiments with pure NC schematics. This paper presents an implementation of NC under a two-way relay model and extends it to two non-straightforward scenarios: (i) multimedia transmission with layered coding and multiple-description coding, and (ii) cognitive radio with Vandermonde frequency division multiplexing (VFDM). The implementation is in real time and based on software-defined radio (SDR). The experimental results show that, by combining NC and source coding, we can control the quality of the received multimedia content in an on-demand manner. Whereas in the VFDM-based cognitive radio, the quality of the received content in the primary receiver is low (due to imperfect channel estimation) yet retrievable. Our implementation results serve as a proof for the practicability of network coding in relevant applications.

Deep semantic segmentation-based multiple description coding

In this paper, we propose a deep semantic segmentation-based multiple description coding (DSSMDC). In the proposed scheme, the input image is divided into two different subsets and getting two descriptions, which is named multiple description pre-processing (MDP). Then, two descriptions are encoded and decoded respectively by utilizing the deep semantic segmentation codec, in which the semantic segmentation label is as side information for improving image reconstruction quality. We can get one side reconstruction, when only one description is received at the decoder. If both descriptions are received at the decoder, we can get the central reconstruction. Experimental results show that the proposed scheme achieves better performance than other existing compression methods.

Recursive Filtering With Measurement Fading: A Multiple Description Coding Scheme

In this article, the recursive filtering problem is studied for a class of discrete-time nonlinear stochastic systems subject to fading measurements. In order to facilitate the data transmission in a resource-constrained communication network, the multiple description coding scheme is adopted to encode the fading measurements into two descriptions with the identical importance. Two independent Bernoulli distributed random variables are introduced to govern the occurrences of the packet dropouts in two channels from the encoders to the decoders. The channel fading phenomenon is characterized by the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$M$</tex-math></inline-formula> th-order Rice fading model whose coefficients are mutually independent random variables obeying certain probability distributions. The purpose of the problem addressed is to design a recursive filter, such that in the simultaneous presence of the stochastic noises, the channel fading and the data coding–decoding mechanism, an upper bound of the filtering error variance is obtained and then minimized at each time step. In virtue of the Riccati difference equation technique and the stochastic analysis approach, the explicit form of the desired filter parameters is derived by solving a sequence of coupled algebraic Riccati-like difference equations. Finally, a simulation experiment is provided to show the applicability of the developed filtering scheme.

MDC-NOMA: Multiple Description Coding-Based Nonorthogonal Multiple Access for Image Transmission

Recently, nonorthogonal multiple access (NOMA) technology has emerged as a key technology for enhancing power and spectrum efficiency of fifth-generation (5G) wireless networks. On the one hand, multiple-description coding (MDC) is a coding technique with high efficiency and strong antiinterference capabilities that can combat burst interference and solve the problem of unreliable transmission due to link impairments and network congestion. In this article, by combining the principles of MDC and NOMA, we propose a hybrid MDC-NOMA scheme to further improve system throughput and transmission robustness. In the proposed scheme, a base station communicates with two users simultaneously over two orthogonal subchannels. In this setup, one subchannel is sufficient to reconstruct an image of acceptable quality. We derive the closed-form expressions for the outage probability and ergodic rate and analyze its peak signal to noise ratio, bit error rate, and visual transmission performance. Furthermore, numerical and simulation results are presented in order to validate the analysis.

HEVC compatible perceptual multiple description video coding for reliable video transmission over packet networks

Multiple description coding (MDC) has been an effective scheme for reliable transmission of videos over error prone networks but requires higher data rates. Recently, perceptual video coding schemes are able to encode videos at a lower data rate, but with the same perceived decoding quality. Such schemes exploit human visual system (HVS) properties to encode videos. Although HVS characteristics have been used in MDC, but only for residual information and are not fully standard compatible. To this end, we propose a high efficiency video coding (HEVC) standard compatible perceptual multiple description video coding (PMDVC) framework. Our proposed framework temporally sub-samples the input video into even and odd frame sub-sequences, which are individually encoded (using HEVC) in a perceptual manner. We encode each description using a context based visual saliency model to obtain visual saliency mask, which is optimally thresholded into salient and non-salient regions. Coding tree unit (CTU) level perceptual relevance mask of each frame is generated by dividing binary saliency mask into five different groups. The quantization parameter at CTU level of each perceptual relevant group is adjusted in such a manner that data rate is minimized while maintaining the perceived quality. Our proposed HEVC based PMDVC scheme is evaluated under lossless and lossy channel conditions. Our results show better performance in data rate reduction, perceptual peak signal-to-noise-ratio, multi- scale structural similarity index, and difference mean opinion score, when compared with HEVC based temporally sub-sampled multiple description video coding scheme.

A weakly secure multiple description coding scheme in lossy multipath channels for fine-grained SVC streaming

Video streaming service is growing rapidly these years. The quality of video streaming may suffer from issues like packet loss and solutions like multiple description coding (MDC) has been shown to provide flexible and distortion-rate optimal video streaming transmission over packet-loss links. On the other hand, the contents of stream are prone to attacks like eavesdropping while MDC is not specifically designed for security purpose. In this paper, fine grain scalably coded video data is channel-coded through multiple description-forward error correction (MD-FEC) coding. The resulting descriptions (packets) are then sent to a variety of channels, which may be peeked by an eavesdropper with certain probability. We adopt the weakly secure design here to reduce the quality of video obtained by the eavesdropper. Two weak security criteria for this problem are proposed, namely the deterministic overhearing peak-signal-to-noise-ratio (PSNR) constraint and the average overhearing PSNR constraint. The corresponding optimization algorithms are provided. Numerical results show that by applying weakly secure design, the PSNR value on the eavesdropper’s side will be reduced to the level at which useful details of the clip can hardly be exposed at the cost of reducing around 1–2 dB at the authorized receiver’s side.

Predictive side decoding for human-centered multiple description image coding

Multiple description coding (MDC) provides a favorable solution for human-centered image communication, which takes into account people’s varying watching situations as well as people’s demand for real-time image display. As an effective technique for MDC, three-description lattice vector quantization (3D-LVQ) is considered for image coding in this paper. Based on intra- and inter-correlation in the 3D-LVQ index assignment as well as wavelet intra-subband correlation, a novel predictive decoding method for 3D-LVQ-based image coding is proposed to enhance side decoding performance, which attempts to predict lost descriptions (sublattice points) in a good way for better reconstructions of wavelet vectors (fine lattice points) in the side decoding. Experimental results validate effectiveness of the proposed decoding scheme in terms of rate-distortion performance.

Convolutional auto-encoder based multiple description coding network

When data is transmitted over an unreliable channel, the error of the data packet may result in serious degradation. The multiple description coding (MDC) can solve this problem and save transmission costs. In this paper, we propose a deep multiple description coding network (MDCN) to realize efficient image compression. Firstly, our network framework is based on convolutional auto-encoder (CAE), which include multiple description encoder network (MDEN) and multiple description decoder network (MDDN). Secondly, in order to obtain high-quality reconstructed images at low bit rates, the encoding network and decoding network are integrated into an end-to-end compression framework. Thirdly, the multiple description decoder network includes side decoder network and central decoder network. When the decoder receives only one of the two multiple description code streams, side decoder network is used to obtain side reconstructed image of acceptable quality. When two descriptions are received, the high quality reconstructed image is obtained. In addition, instead of quantization with additive uniform noise, and SSIM loss and distance loss combine to train multiple description encoder networks to ensure that they can share structural information. Experimental results show that the proposed framework performs better than traditional multiple description coding methods.

Cross-layer Optimization for Video Transmission using MDC in Wireless Mesh Networks

Abstract In this paper, we propose a cross-layer optimization technique for improving the QoS of video streaming applications in multi-radio Wireless Mesh Networks (WMNs) using Multiple Description Coding (MDC). WMN is an emerging technology which is used to connect various types of networks to the internet. As the trafficdensity is very high fromthe client mesh to the gateways, load balancing in these networks has become an important research issue. Thus, there is a need for multipath routing which can exploit the multi-radio capabilities along with the load balancing mechanism. Furthermore, the dynamic and shared nature of wireless medium makes the task of supporting QoS for video streaming applications challenging. Towards this,MDCis an effective technique for the video transmission over the unpredictable routes because of varying channel conditions.In this work,we compute multiple paths using Passive Interference andDelay Aware (PIDA) metric and performload balancing using MDC. Proposed work is implemented in Ad hoc On-demand Multipath Distance Vector (AOMDV) routing protocol using NS2 simulator. The results reveal that proposed technique withMDCperforms better in terms of PSNR, frame delay and frame loss compared to existing technique

A New Polyphase Down-Sampling Based Multiple Description Image Coding.

Multiple description coding (MDC) is an efficient source coding technique for error-prone transmission over multiple channels. In this paper, we focus on the design of a new polyphase down-sampling based MDC (NPDS-MDC) for image signals. The encoding of our proposed NPDS-MDC consists of three steps. First, we perform down-sampling on each N×N image block according to the quincunx down-sampling pattern. Second, we propose a new transform and apply it to the down-sampled pixels to produce the side descriptions. Third, we develop an error compensation algorithm to reduce the compression distortion occurring on the down-sampled pixels. In our scheme, the side decoding is performed posterior to image interpolation with reference to the down-sampled compressed pixels. Moreover, the central decoding is achieved by interlacing the side descriptions. We also propose a compression-constrained central deblocking algorithm to further improve the efficiency of the central decoding. The experimental results indicate that our proposed MDC scheme offers clearly superior performance, especially at high bit rates, as compared to the state-of-the-art methods for various types of images.

On the Compound Broadcast Channel: Multiple Description Coding and Interference Decoding

This work investigates the general two-user Compound Broadcast Channel (BC) where an encoder wishes to transmit common and private messages to two receivers while being oblivious to two possible channel realizations controlling the communication. The focus is on the characterization of the largest achievable rate region by resorting to more evolved encoding and decoding techniques than the conventional coding for the standard BC. The role of the decoder is first explored, and an achievable rate region is derived based on the principle of "Interference Decoding" (ID) where each receiver decodes its intended message and chooses to (non-uniquely) decode or not the interfering message. This inner bound is shown to be capacity achieving for a class of non-trivial compound BEC/BSC broadcast channels while the worst-case of Marton's inner bound -based on "Non Interference Decoding" (NID)- fails to achieve the capacity region. The role of the encoder is then studied, and an achievable rate region is derived based on "Multiple Description" (MD) coding where the encoder transmits a common as well as multiple dedicated private descriptions to the many instances of the users channels. It turns out that MD coding outperforms the single description scheme -Common Description (CD) coding- for a class of compound Multiple Input Single Output Broadcast Channels (MISO BC).

On the Compound Broadcast Channel: Multiple Description Coding and Interference Decoding

This work investigates the general two-user compound Broadcast Channel (BC) in which an encoder wishes to transmit two private messages W1 and W2 to two receivers while being oblivious to the actual channel realizations controlling the communication. The focus is on the characterization of the largest achievable rate region by resorting to more involved encoding and decoding techniques than the usual coding schemes of the standard BC. Involved decoding schemes are first explored, and an achievable rate region is derived based on the principle of Interference Decoding (ID), in which each receiver decodes its intended message and chooses to (non-uniquely) decode, or not, the interfering non-itended message. This decoding scheme is shown to be capacity achieving for a class of non-trivial compound BEC/BSC broadcast channels while the worst-case of Marton’s inner bound—based on No Interference Decoding (NID)—fails to achieve the capacity region. Involved encoding schemes are later investigated, and an achievable rate region is derived based on Multiple Description (MD) coding wherin the encoder transmits a common description as well as multiple dedicated private descriptions to the many possible channel realizations of the users. It turns out that MD coding yields larger inner bounds than the single description scheme—Common Description (CD) coding—for a class of compound Multiple Input Single Output Broadcast Channels (MISO BC).