dPeer-to-peer networks (P2P) form a distributed communication infrastructure that is particularly well matched to video streaming using multiple description coding. We form M descriptions using MDC-FEC building on a s...
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ISBN:
(纸本)0819459763
dPeer-to-peer networks (P2P) form a distributed communication infrastructure that is particularly well matched to video streaming using multiple description coding. We form M descriptions using MDC-FEC building on a scalable version of the "Dirac" video coder. The M descriptions are streamed via M different application layer multicast (ALM) trees embedded in the P2P network. Client nodes (peers in the network) receive a number of descriptions m < M that is dependent on their bandwidth. In this paper we consider the optimization of the received video qualities, taking into account the distribution of the clients' bandwidth. We propose three "fairness" criteria to define the criterion to be optimized. Numerical results illustrate the effects of the different fairness criteria and client bandwidth distributions on the rates allocated to the compressed video layers and multipledescriptions.
In the lossy coding of perceptually relevant signals, such as sound and im- ages, the ultimate goal is to achieve good perceived quality of the recon- structed signal, under a constraint on the bit-rate. Conventional ...
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In the lossy coding of perceptually relevant signals, such as sound and im- ages, the ultimate goal is to achieve good perceived quality of the recon- structed signal, under a constraint on the bit-rate. Conventional method- ologies focus either on a rate-distortion optimization or on the preservation of signal features. Technologies resulting from these two perspectives are efficient only for high-rate or low-rate scenarios. In this dissertation, a new objective is proposed: to seek the optimal rate-distortion trade-off under a constraint that statistical properties of the reconstruction are similar to those of the source. The new objective leads to a new quantization concept: distribution preserving quantization (DPQ). DPQ preserves the probability distribution of the source by stochastically switching among an ensemble of quantizers. At low rates, DPQ exhibits a synthesis nature, resembling existing cod- ing methods that preserve signal features. Compared with rate-distortion optimized quantization, DPQ yields some rate-distortion performance for perceptual benefits. The rate-distortion optimization for DPQ facilitates mathematical anal- ysis. The dissertation defines a distribution preserving rate-distortion func- tion (DP-RDF), which serves as a lower bound on the rate of any DPQ method for a given distortion. For a large range of sources and distortion measures, the DP-RDF approaches the classic rate-distortion function with increasing rate. This suggests that, at high rates, an optimal DPQ can ap- proach conventional quantization in terms of rate-distortion characteristics. After verifying the perceptual advantages of DPQ with a rela- tively simple realization, this dissertation focuses on a method called transformation-based DPQ, which is based on dithered quantization and a non-linear transformation. Asymptotically, with increasing dimensional- ity, a transformation-based DPQ achieves the DP-RDF for i. i. d. Gaussian sources and the mean squared error (MSE)
Multimedia communication system design encounters great challenges in network congestion and delay sensibility issues. multiple description coding system has recently emerged as a desirable framework for robust multim...
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ISBN:
(纸本)9781509025978
Multimedia communication system design encounters great challenges in network congestion and delay sensibility issues. multiple description coding system has recently emerged as a desirable framework for robust multimedia data transmission over the unreliable channels. This paper presents a prediction method of a lost label during transmission called lost label prediction algorithm in order to improve performance of side decoders when there always two of the three channels successfully transmitting the data. The lost label is predicted by putting on the nearest sublattice point between the two available labels. Simulation results show that the improved three descriptions lattice vector quantization system provides lower distortion and better reconstruction quality.
In this paper, we present a polar coding scheme for the multiple description coding problem. The proposed scheme improves upon the existing joint polarization based scheme by Shi, Song, Tian, Chen, and Dumitrescu and ...
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ISBN:
(纸本)9781538632666
In this paper, we present a polar coding scheme for the multiple description coding problem. The proposed scheme improves upon the existing joint polarization based scheme by Shi, Song, Tian, Chen, and Dumitrescu and achieves the entire El Gamal-Cover inner bound for this problem.
multiple description coding (MDC) combined with multipath transmission is a viable solution to the growing demand of reliable multimedia video communication over the Internet. Despite the progress in MDC techniques, t...
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ISBN:
(纸本)9781424404810
multiple description coding (MDC) combined with multipath transmission is a viable solution to the growing demand of reliable multimedia video communication over the Internet. Despite the progress in MDC techniques, transport protocols based on TCP cannot efficiently handle multipath transmissions of this kind of traffic. In this paper we present MD-SCTP, a full-multipath partially-reliable SCTP-based protocol, providing different scheduling schemes and featuring a selective retransmission within time-to-delivery constraints of multimedia traffic. Performance analysis proves the validity of our scheduler and of our selective retransmission scheme.
The rate performance of wireless coded caching schemes is typically limited by the lowest achievable per-user rate in the given multicast group, during each transmission time slot. In this paper, we provide a new code...
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ISBN:
(纸本)9781728154787
The rate performance of wireless coded caching schemes is typically limited by the lowest achievable per-user rate in the given multicast group, during each transmission time slot. In this paper, we provide a new coded caching scheme, alleviating this worst-user effect for the prominent case of multimedia applications. In our scheme, instead of maximizing the symmetric rate among all served users, we maximize the total quality of experience (QoE);where QoE at each user is defined as the video quality perceived by that user. We show the new scheme requires solving an NP-hard optimization problem. Thus, we provide two heuristic algorithms to solve it in an approximate manner;and numerically demonstrate the near-optimality of the proposed approximations. Our approach allows flexible allocation of distinct video quality for each user, making wireless coded caching schemes more suitable for real-world implementations.
Block compressed sensing (BCS) is a new research branch in compressed sensing, which is famous for its superior performances. Evaluations between compression and reconstructed quality are based on the error- free tran...
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ISBN:
(纸本)9781538663097
Block compressed sensing (BCS) is a new research branch in compressed sensing, which is famous for its superior performances. Evaluations between compression and reconstructed quality are based on the error- free transmission, and we look for the error resilient transmission of BCS over lossy channels. We propose to employ multiple description coding (MDC) to protect the BCS coefficients at the encoder. Then, protected coefficients are ready for transmitting over multiple lossy channels. Finally, we apply the capability of MDC and the high correlations between color planes for image reconstruction. Simulations have presented the enhancements of protected image qualities for the proposed algorithm.
This paper presents a layered error resilient scheme for Set Partitioning in Hierarchical Trees (SPIHT) coding which incorporates the multiple description coding (MDC) into the data partition. The major feature of thi...
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ISBN:
(纸本)9783037850275
This paper presents a layered error resilient scheme for Set Partitioning in Hierarchical Trees (SPIHT) coding which incorporates the multiple description coding (MDC) into the data partition. The major feature of this scheme is that the MDC is adopted in the process of packetizing the spatial orientation trees, so as to protect the important information bits according to different importance and channel state. The proposed scheme can allocate redundancy accurately and flexibly, by differentiating importance of bits through different bit planes. Experimental results show that the proposed method achieves good performance over packet erasure channels.
Digital watermarking is one of the useful solutions for digital rights management systems, and it is also a popular research topic in the last decade. However, most watermarking related literature focus on how to resi...
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ISBN:
(纸本)0819459763
Digital watermarking is one of the useful solutions for digital rights management systems, and it is also a popular research topic in the last decade. However, most watermarking related literature focus on how to resist intentional attacks by applying benchmarks to watermarked media to estimate the effectiveness of the watermarking algorithm. Only a few papers concentrate on the error resilient transmission of watermarked media. In this paper, we propose an innovative algorithm on vector quantization (VQ) based image watermarking, suitable for error-resilient transmission over noisy channels. By incorporating watermarking with multiple description coding (MDC), our proposed schemes for embedding multiple watermarks can efficiently overcome channel impairments while retaining the capability for copyright and ownership protection. In addition, we employ one optimization technique, called tabu search, to optimize both the watermarked image quality, and the robustness of the extracted watermarks. Simulations demonstrate the utility and practicability of our proposed algorithm.
The compressed sensing paradigm allows to efficiently represent sparse signals by means of their linear measurements. However, the problem of transmitting these measurements to a receiver over a channel potentially pr...
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ISBN:
(纸本)9781479903566
The compressed sensing paradigm allows to efficiently represent sparse signals by means of their linear measurements. However, the problem of transmitting these measurements to a receiver over a channel potentially prone to packet losses has received little attention so far. In this paper, we propose novel methods to generate multipledescriptions from compressed sensing measurements to increase the robustness over unreliable channels. In particular, we exploit the democracy property of compressive measurements to generate descriptions in a simple manner by partitioning the measurement vector and properly allocating bit-rate, outperforming classical methods like the multipledescription scalar quantizer. In addition, we propose a modified version of the Basis Pursuit Denoising recovery procedure that is specifically tailored to the proposed methods. Experimental results show significant performance gains with respect to existing methods.
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