The rate-distortion-equivocation region has been derived recently for the Heegard-Berger problem, in which only one of the decoders has access to the correlated side information, under the constraint of the side infor...
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ISBN:
(纸本)9781665450850
The rate-distortion-equivocation region has been derived recently for the Heegard-Berger problem, in which only one of the decoders has access to the correlated side information, under the constraint of the side information privacy which is desired to keep the side information private from the uninformed decoder. In this paper, this result is extended to two special cases of the scalable source coding problem, in which the encoder sends a two-layer description to two decoders such that the first layer can be received by both two decoders, while the second is only for one of two decoders. For the first case when the second-layer description is only available at the informed decoder, the set of all feasible rate-distortion-equivocation is characterized under the constraint of the side information privacy. For the other case when the second-layer description is only at the uninformed decoder, the inner bound and the outer bound of the rate-distortion-equivocation region are provided under the constraint of the side information privacy.
We consider the problem of side-information scalable (SI-scalable) sourcecoding, where the encoder constructs a two-layer description, such that the receiver with high quality side information will be able to use onl...
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We consider the problem of side-information scalable (SI-scalable) sourcecoding, where the encoder constructs a two-layer description, such that the receiver with high quality side information will be able to use only the first layer to reconstruct the source in a lossy manner, while the receiver with low quality side information will have to receive both layers in order to decode. We provide inner and outer bounds to the rate-distortion (R-D) region for general discrete memoryless sources. The achievable region is tight when either one of the decoders requires a lossless reconstruction, and when the distortion measures are degraded and deterministic. Furthermore, the gap between the inner and the outer bounds can be bounded by certain constants when the squared error distortion measure is used. The notion of perfect scalability is introduced, for which necessary and sufficient conditions are given for sources satisfying a mild support condition. Using SI-scalablecoding and successive refinement Wyner-Ziv coding as basic building blocks, we provide a complete characterization of the rate-distortion region for the important quadratic Gaussian source with multiple jointly Gaussian side informations, where the side information quality is not necessarily monotonic along the scalablecoding order. A partial result is provided for the doubly symmetric binary source under the Hamming distortion measure when the worse side information is a constant, for which one of the outer bounds is strictly tighter than the other.
Multirate multicast is a powerful methodology of multimedia communication in heterogenous networks. A variant of multirate multicast motivated by scalable multimedia streaming is layered multicast, where the transmitt...
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Multirate multicast is a powerful methodology of multimedia communication in heterogenous networks. A variant of multirate multicast motivated by scalable multimedia streaming is layered multicast, where the transmitted signal is presented in successive data layers. With recent advances of network coding theory, many layered multicast schemes using network coding have been proposed to improve the performance of traditional routing-based layered multicast. They divide the network into different layers and construct a unirate multicast network code for each layer. However, these schemes do not perform network coding between data layers, and consequently cannot realize the full potential of network coding. In this paper, we propose a novel approach to layered multicast that allows network coding of data in different layers. This relaxation lends the proposed scheme greater flexibility in optimizing the data flow than previous layered solutions, and thus achieves higher throughput.
This paper proposes an optimized, low-complexity methodology that combines Joint source-Channel coding (JSCC) based on Forward Error Correction (FEC) coding and scalable Multiple Description coding (MDC) mechanisms fo...
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ISBN:
(纸本)9781424436095
This paper proposes an optimized, low-complexity methodology that combines Joint source-Channel coding (JSCC) based on Forward Error Correction (FEC) coding and scalable Multiple Description coding (MDC) mechanisms for error-resilient data transmission over error-prone packet-based channels. Additionally, we report a comparative theoretical analysis between (i) MDC, and FEC-based scalable JSCC for sources encoded using (ii) Single Description coding (SDC) and (iii) MDC. Our analysis assumes ideal source coders that can achieve the theoretical performance bounds for a Gaussian source. This source model is independent of the actual implementation and therefore allows to draw conclusions on the theoretical performance of these approaches and to determine which methodology should be employed in specific transmission scenarios.
In this paper we examine the Distortion-Rate (D-R) performance of two competing approaches for error-resilient transmission of scalablesources over error-prone packet-based memoryless channels. Thereby, we consider s...
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ISBN:
(纸本)9781424432974
In this paper we examine the Distortion-Rate (D-R) performance of two competing approaches for error-resilient transmission of scalablesources over error-prone packet-based memoryless channels. Thereby, we consider scalable Joint source-Channel coding (JSCC) based on Forward Error Correction (FEC) and scalable Multiple Description coding (MDC). Our analysis considers memoryless Gaussian input sources encoded using source coders that can achieve theoretical performance bounds. This input source model is independent of actual implementations of the source coders and therefore allows drawing conclusions on the theoretical D-R performance of both approaches. Our comparative analysis indicates that in matched channel conditions, the use of an optimized FEC-based JSCC approach yields significantly better error resilience compared to the use of scalable MDC. Moreover, it is shown that in mismatched conditions a scalable JSCC approach has the potential to outperform a scalable MDC approach.
To provide unequal erasure protection to scalable codes, a general framework has been proposed in [1] and it has become the foundation of following research in this literature. In this paper, we make opportunistic uti...
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ISBN:
(纸本)9781605586212
To provide unequal erasure protection to scalable codes, a general framework has been proposed in [1] and it has become the foundation of following research in this literature. In this paper, we make opportunistic utilization of received packets under the same framework. Specifically, we extract those non-decodable original symbols in received packets by taking advantage of the joint coding structure. By regulating the scalable codes to partially-decodable scalable codes, these original symbols can be used to improve the quality of reconstructed source. Further more, we formulate the opportunistic unequal erasure protection and analyze the relationship between optimal unequal erasure protection (OP) and opportunistic optimal unequal erasure protection (OOP). Based on the analysis result, a simple algorithm is proposed to find the optimal protection which maximizes the expected quality of reconstructed source. Finally, experiment results are presented which verify the improvement of opportunistic utilization over traditional unequal erasure protection.
The common practice for achieving unequal error protection (UEP) in scalable multimedia communication systems is to design rate-compatible punctured channel codes before computing the UEP rate assignments. This paper ...
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The common practice for achieving unequal error protection (UEP) in scalable multimedia communication systems is to design rate-compatible punctured channel codes before computing the UEP rate assignments. This paper proposes a new approach to designing powerful irregular repeat accumulate (IRA) codes that are optimized for the multimedia source and to exploiting the inherent irregularity in IRA codes for UEP. Using the end-to-end distortion due to the first error bit in channel decoding as the cost function, which is readily given by the operational distortion-rate function of embedded source codes, we incorporate this cost function into the channel code design process via density evolution and obtain IRA codes that minimize the average cost function instead of the usual probability of error. Because the resulting IRA codes have inherent UEP capabilities due to irregularity, the new IRA code design effectively integrates channel code optimization and UEP rate assignments, resulting in source-optimized channel coding or joint source-channel coding. We simulate our source-optimized IRA codes for transporting SPIHT-coded images over a binary symmetric channel with crossover probability p. When p = 0.03 and the channel code length is long (e.g., with one codeword for the whole 512 x 512 image), we are able to operate at only 9.38% away from the channel capacity with code length 132380 bits, achieving the best published results in terms of average peak signal-to-noise ratio (PSNR). Compared to conventional IRA code design (that minimizes the probability of error) with the same code rate, the performance gain in average PSNR from using our proposed source-optimized IRA code design is 0.8759 dB when p = 0.1 and the code length is 12800 bits. As predicted by Shannon's separation principle, we observe that this performance gain diminishes as the code length increases.
The common practice for achieving unequal error protection (UEP) in scalable multimedia communication systems is to design rate-compatible punctured channel codes before computing the UEP rate assignments. This paper ...
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The common practice for achieving unequal error protection (UEP) in scalable multimedia communication systems is to design rate-compatible punctured channel codes before computing the UEP rate assignments. This paper proposes a new approach to designing powerful irregular repeat accumulate (IRA) codes that are optimized for the multimedia source and to exploiting the inherent irregularity in IRA codes for UEP. Using the end-to-end distortion due to the first error bit in channel decoding as the cost function, which is readily given by the operational distortion-rate function of embedded source codes, we incorporate this cost function into the channel code design process via density evolution and obtain IRA codes that minimize the average cost function instead of the usual probability of error. Because the resulting IRA codes have inherent UEP capabilities due to irregularity, the new IRA code design effectively integrates channel code optimization and UEP rate assignments, resulting in source-optimized channel coding or joint source-channel coding. We simulate our source-optimized IRA codes for transporting SPIHT-coded images over a binary symmetric channel with crossover probability p. When p = 0.03 and the channel code length is long (e.g., with one codeword for the whole 512 x 512 image), we are able to operate at only 9.38% away from the channel capacity with code length 132380 bits, achieving the best published results in terms of average peak signal-to-noise ratio (PSNR). Compared to conventional IRA code design (that minimizes the probability of error) with the same code rate, the performance gain in average PSNR from using our proposed source-optimized IRA code design is 0.8759 dB when p = 0.1 and the code length is 12800 bits. As predicted by Shannon's separation principle, we observe that this performance gain diminishes as the code length increases.
A joint source/channel coding algorithm is proposed for the transmission of multiple image sources over memoryless channels. The proposed algorithm uses a quality scalable image coder to optimally allocate a limited b...
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A joint source/channel coding algorithm is proposed for the transmission of multiple image sources over memoryless channels. The proposed algorithm uses a quality scalable image coder to optimally allocate a limited bit budget among all the sources to achieve the optimal overall distortion reduction for the multiple reconstructed images. In addition to the conventional un gain, it provides channel multiplexing gain, which can be much more significant. Furthermore, an extended scheme is proposed to provide flexibility between the optimization performance and complexity.
This correspondence focuses on a significant distinction between two hierarchical type covering strategies, namely, weak and strong covering, and on the impact of this distinction on known results. In particular, it i...
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This correspondence focuses on a significant distinction between two hierarchical type covering strategies, namely, weak and strong covering, and on the impact of this distinction on known results. In particular, it is demonstrated that the rate region for weak covering, whose natural use is in scalable source coding, is generally larger than the rate region for strong covering, which is primarily useful in hierarchical guessing. This correspondence also presents a corrected converse result for the hierarchical guessing problem.
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