Scalable Multiple Description Research Articles

Adaptively post-encoding multiple description video coding

In video coding and transmission, the network conditions are crucial, i.e., bandwidth, delay and other factors. However, how to effectively take these factors into account is still a challenge, as heterogeneous networks are dynamic, and therefore it is difficult to predict their changes. This paper first reports a post-encoding of Scalable Multiple Description Coding (SMDC), which is towards self-adaptive video delivery under different conditions of the network. The proposed scheme contains three major steps: (1) spatiotemporal wavelet transformation of input video sequence; (2) context-based adaptive binary arithmetic coding; and (3) rate allocation under the conditions of the network and analysis of the principle relationship of the rate–distortion slope ratio with packet-loss probability in network links. The performance of the SMDC is compared with that of scalable video coding and scalable H.264, and SMDC is demonstrated to effectively optimize the video delivery to adapt to the dynamics of heterogeneous networks. Part of this work has been published on Data Compression Conference 2009 as a short abstract version [37].

Design of a service platform for delay-sensitive video streaming applications based on multicast p2p and scalable MDC encoding

The great diffusion of Internet accesses in the world and the enormous evolution of the Internet technologies have strongly determined dissemination and consolidation of many applications of video content distribution. However, multicast real-time video communications for interactive service applications with a very high number of users, like for example multipoint videoconferences and interactive video games, remains a challenging research topic for the presence of very strict requirements in terms of end-to-end delay and perceived quality.The target of this paper is to propose a video distribution platform that is able to provide a huge number of users with a delay constrained multicast video streaming. To this purpose, the proposed content delivery platform is based on a peer-to-peer approach that exploits multicast overlay organization of the peers to address the challenges due to bandwidth heterogeneity. To improve reliability and flexibility, video is coded using a scalable multiple description approach. Some design guidelines are provided taking into account some requirements in terms of delay, average PSNR, robustness against underlying network bandwidth fluctuations, and fairness.

Symmetric Scalable Multiple Description Scalar Quantization

Real-time data delivery over best-effort error-prone packet networks has invigorated the study of robust coding schemes, such as scalable multiple description coding (SMDC). In this context, the paper introduces a novel generic symmetric scalable multiple description quantizer (SSMDSQ) which generates perfectly balanced source descriptions. Novel embedded index assignments are proposed which are used to realize high, as well as medium-to-low redundancy SSMDSQs. Compared to existing designs, it is shown that the proposed quantizer constructions exhibit superior distortion-rate (D-R) performance. Moreover, this paper describes an innovative extension of the Lloyd-Max algorithm in order to optimize symmetric and asymmetric scalable multiple description quantizers. For a family of Generalized Gaussian (GG) source distributions, the proposed optimization algorithm yields on average a significant D-R performance gain over unoptimized quantizers. Furthermore, anchored in the designed SSMDSQs, an SMDC framework is established to realize packet-based transmission over erasure channels. In this framework, transmission strategies are determined for scenarios wherein the average packet loss rate over the transmission link is (a) unknown and (b) can be estimated at the encoder. For both scenarios, SMDC packetized transmission is simulated for a family of GG distributions. Experimental results confirm that, compared to contemporary schemes, the designed quantizer constructions (with or without optimization) account for a significant average gain in signal-to-noise ratio (SNR) for a wide range of packet loss rates.

Redundancy controllable scalable unbalanced multiple description bitstream generation for peer-to-peer video streaming

In peer-to-peer video streaming, the robustness to peer and packet losses is regarded very important in order to enjoy a good quality of experience. Multiple description coding (MDC) schemes are known to provide high robustness to packet losses. In peer-to-peer streaming in addition to high robustness, efficient controllability of data rate and redundancy among the data streams from peers is also vital. In this paper, a novel framework for scalable multiple description coding scheme for peer-to-peer video streaming is presented by addressing these requirements. The proposed MDC solution is based on the multiple description scalar quantization (MDSQ) by addressing the joint decoding of unbalanced descriptions and addition of jointly decodable successive refinement layers to side descriptions. Firstly, the design conditions for MDSQ with constrained successive refinement to obtain scalable multiple description streams where the bit streams can be truncated at any point to obtain lower quality spatial temporal descriptions are firstly proposed. Then the design conditions for joint decoding of two or more side descriptions from different multiple description scalar quantizers, originating from various bin spread factors leading to controllable redundancy are proposed. These design conditions enable joint redundancy and data rate control for streams coming from different peers, thereby, enabling high robustness to packet losses as well as peer losses with the adaptability of redundancy levels and truncation of scalable streams. The proposed design constraints are used within the motion compensated temporal filtering (MCTF) framework to demonstrate its advancement in robust peer-to-peer video streaming. The results show significant improvements over conventional MDC based on simple MSDQ and over single description scalable video.

A P2P Platform for Real-Time Multicast Video Streaming Leveraging on Scalable Multiple Descriptions to Cope with Bandwidth Fluctuations

In the immediate future video distribution applications will increase their diffusion thanks to the ever-increasing user capabilities and improvements in the Internet access speed and performance. The target of this paper is to propose a content delivery system for real-time streaming services based on a peer-to-peer approach that exploits multicast overlay organization of the peers to address the challenges due to bandwidth heterogeneity. To improve reliability and flexibility, video is coded using a scalable multiple description approach that allows delivery of sub-streams over multiple trees and allows rate adaptation along the trees as the available bandwidth changes. Moreover, we have deployed a new algorithm for tree-based topology management of the overlay network. In fact, tree based overlay networks better perform in terms of end-to-end delay and ordered delivery of video flow packets with respect to mesh based ones. We also show with a case study that the proposed system works better than similar systems using only either multicast or multiple trees.

A Scalable Multiple Description Scheme for 3D Video Coding Based on the Interlayer Prediction Structure

The most recent literature indicates multiple description coding (MDC) as a promising coding approach to handle the problem of video transmission over unreliable networks with different quality and bandwidth constraints. Furthermore, following recent commercial availability of autostereoscopic 3D displays that allow 3D visual data to be viewed without the use of special headgear or glasses, it is anticipated that the applications of 3D video will increase rapidly in the near future. Moving from the concept of spatial MDC, in this paper we introduce some efficient algorithms to obtain 3D substreams that also exploit some form of scalability. These algorithms are then applied to both coded stereo sequences and to depth image-based rendering (DIBR). In these algorithms, we first generate four 3D subsequences by subsampling, and then two of these subsequences are jointly used to form each of the two descriptions. For each description, one of the original subsequences is predicted from the other one via some scalable algorithms, focusing on the inter layer prediction scheme. The proposed algorithms can be implemented as pre- and postprocessing of the standard H.264/SVC coder that remains fully compatible with any standard coder. The experimental results presented show that these algorithms provide excellent results.

SVC-based scalable multiple description video coding and optimization of encoding configuration

It is well known that multiple multicast trees can avoid single point of failures in peer-to-peer (P2P) streaming originating from a single source by providing path diversity. Multiple description video coding is well suited for serving video over multiple multicast trees, such that each description can be streamed over a different tree. In scalable multiple description coding (SMDC), each description is scalable coded (e.g., derived from a single scalable video coding (SVC)-compliant bitstream) so that descriptions can be efficiently adapted to the available rate of each link for effective congestion control. This paper proposes (i) new SMDC generation methods based on various combinations of video segments (GOPs or fames) coded at high and low rates (one or more layers) and (ii) a multiple-objective optimization (MOO) framework for selection of the best encoding configuration of the proposed SMDC from a set of candidates in order to achieve the best tradeoff between redundancy and reliability (measured by end-to-end rate-distortion performance over a range of extraction points for a set of packet loss probabilities), while maximizing the range of extraction points of each scalable description. The optimization is performed over selected SVC encoding parameters and MD generation alternatives that feature various levels of redundancy at a fixed total rate for all descriptions. The framework is generic to allow optimization over other SVC encoding variables and MD generation methods, or just over the SVC encoding variables without MD, if desired. Results of Monte-Carlo simulation of SMDC streaming with two descriptions over two paths with packet losses are provided to demonstrate performance of the proposed methods.

Scalable multiple description video coding for stereoscopic 3D

Scalable multiple description video coding (MDC) provides adaptability to bandwidth variations and receiving device characteristics, and can improve error robustness in multimedia networks. In this paper, a scalable MDC scheme is proposed for stereoscopic 3D video. Scalable MDC has previously been applied to 2D video but not to 3D video. The proposed algorithm enhances the error resilience of the base layer of the scalable video coding (SVC) standard using even and odd frame based MDC. The performance of the algorithm is evaluated in error free and error prone environments. Simulation results show improved performance using the proposed scalable MDC at high error rates compared to the original SVC. To improve the rate distortion performance, down-sampling of the depth information is proposed for SVC and scalable MDC. The proposed method reduces the overall bit rates and consequently: (1) improves their rate distortion, particularly at lower bit rates in error free channels; and (2) improves their performance in error prone channels.

Scalable Multiple-Description Image Coding Based on Embedded Quantization

Scalable multiple-description (MD) coding allows for fine-grain rate adaptation as well as robust coding of the input source. In this paper, we present a new approach for scalable MD coding of images, which couples the multiresolution nature of the wavelet transform with the robustness and scalability features provided by embedded multiple-description scalar quantization (EMDSQ). Two coding systems are proposed that rely on quadtree coding to compress the side descriptions produced by EMDSQ. The proposed systems are capable of dynamically adapting the bitrate to the available bandwidth while providing robustness to data losses. Experiments performed under different simulated network conditions demonstrate the effectiveness of the proposed scalable MD approach for image streaming over error-prone channels.

Scalable Multiple-Description Image Coding Based on Embedded Quantization

Scalable Multiple-Description Image Coding Based on Embedded Quantization

Scalable multiple description coding and distributed video streaming in 3G mobile communications

AbstractThis paper proposes a distributed multimedia delivery mobile network for video streaming in 3rd generation (3G) mobile communications. The joint design of layered coding (LC) and multiple description coding (MDC) is employed to address the bandwidth fluctuations and packet loss problems in the wireless network and to further enhance the error resilience tools in MPEG‐4. A new Internet protocol (IP) differentiated services (DiffServ) video marking algorithm is presented to support an unequal error protection of the LC components. Both intra‐RAN (radio access network) handoff and inter‐RAN handoff procedures are discussed, which provide path diversity to combat streaming video outage due to handoff in the universal mobile telecommunications system (UMTS). Computer simulation results demonstrate that: (1) the newly proposed IP DiffServ video marking algorithm is more suitable for video streaming in an IP mobile network as compared with the previously proposed algorithm, and (2) the proposed handoff procedures have better performance in terms of handoff latency, end‐to‐end delay and handoff scalability than that in UMTS. Copyright © 2005 John Wiley & Sons, Ltd.