We propose a distributed binary arithmetic coder for Slepian-Wolf coding with decoder side information, along with a soft joint decoder. The proposed scheme provides several advantages over existing schemes, and its p...
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We propose a distributed binary arithmetic coder for Slepian-Wolf coding with decoder side information, along with a soft joint decoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths.
In the paper we advocate image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: classical image compression is considered from the positions o...
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ISBN:
(纸本)0819452114
In the paper we advocate image compression technique in the scope of distributed source coding framework. The novelty of the proposed approach is twofold: classical image compression is considered from the positions of sourcecoding with side information and, contrarily to the existing scenarios, where side information is given explicitly, side information is created based on deterministic approximation of local image features. We consider an image in the transform domain as a realization of a source with a bounded codebook of symbols where each symbol represents a particular edge shape. The codebook is image independent and plays the role of auxiliary source. Due to the partial availability of side information at both encoder and decoder we treat our problem as a modification of Berger-Flynn-Gray problem and investigate a possible gain over the solutions when side information is either unavailable or available only at decoder. Finally. we present a practical compression algorithm for passport photo images based on our concept that demonstrates the superior performance in very low bit rate regime.
We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problems. As a corollary, this inequality yields a...
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ISBN:
(纸本)1424405041
We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problems. As a corollary, this inequality yields a generalization of the classical entropy-power inequality (EPI). As another corollary, this inequality sheds insight into maximizing the differential entropy of the sum of two dependent random variables.
In the Shannon-theoretic analysis of joint source-channel coding problems, achievability is usually established via a two-stage approach: The sources are compressed into bits' and these bits are reliably communica...
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ISBN:
(纸本)9781424415632
In the Shannon-theoretic analysis of joint source-channel coding problems, achievability is usually established via a two-stage approach: The sources are compressed into bits' and these bits are reliably communicated across the noisy channels. Random coding arguments are the backbone of both stages of the proof. This strategy not only establishes the optimal performance for stationary ergodic point-to-point problems, but also for a number of simple network situations, such as independent sources that are communicated with respect to separate fidelity criteria across a multiple-access channel. Beyond such simple cases, for general networks, unstructured random coding arguments are not sufficient. This was first realized for sourcecoding by Korner and Marton, who showed that for a distributed source coding problem where one only needs to recover a function of the sources random linear codes are necessary. The goal of this note is to extend this insight to pure channel coding as well as to joint source-channel coding problems, such as the problem of reliable computation over a multiple-access channel and a multi-access network with relays.
distributed source coding is a new paradigm for source compression, based on the information-theoretic results built upon by Slepian and Wolf, and Wyner and Ziv from the 1970s. Recently some practical applications of ...
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ISBN:
(纸本)9783540694212
distributed source coding is a new paradigm for source compression, based on the information-theoretic results built upon by Slepian and Wolf, and Wyner and Ziv from the 1970s. Recently some practical applications of distributed source coding to video compression have been studied due to its advantage of lower encoding complexity over conventional video coding standards. In this paper, we proposed a new distributed source coding framework based on signal denoising techniques. To apply the proposed framework in video coding systems, we give a novel distributed video coding scheme. Our,experimental results show that the proposed scheme can achieve better coding efficiency while keeping the simple encoding property.
In this paper, we propose a distributed compression approach for multi-view images, where each camera efficiently encodes its visual information locally without requiring any collaboration with the other cameras. Such...
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ISBN:
(纸本)9781424414369
In this paper, we propose a distributed compression approach for multi-view images, where each camera efficiently encodes its visual information locally without requiring any collaboration with the other cameras. Such a compression scheme can be necessary for camera sensor networks, where each camera has limited power and communication resources and can only transmit data to a central base station. The correlation in the multi-view data acquired by a dense multi-camera system can be extremely large and should therefore be exploited at each encoder in order to reduce the amount of data transmitted to the receiver. Our distributed source coding approach is based on a quadtree decomposition method and uses some geometrical information about the scene and the position of the cameras to estimate this multi-view correlation. We assume that the different views can be modelled as 2D piecewise polynomial functions with 1D linear boundaries and show how our approach applies in this context. Our simulation results show that our approach outperforms independent encoding of real multi-view images.
We address the problem of compressing correlated distributedsources, i.e., correlated sources which are not co-located or which cannot cooperate to directly exploit their correlation. In this paper, we consider the r...
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We address the problem of compressing correlated distributedsources, i.e., correlated sources which are not co-located or which cannot cooperate to directly exploit their correlation. In this paper, we consider the related problem of compressing a source which is correlated with another source that is available only at the decoder. This problem has been studied in the information theory literature under the name of the Slepian-Wolf sourcecoding problem for the lossless coding case, and as ''rate-distortion with side information" for the lossy coding case. In this work, we provide a constructive practical framework based on algebraic trellis codes dubbed as distributed source coding Using Syndromes (DISCUS), that can be applicable in a variety of settings. Simulation results are presented for sourcecoding of independent and identically distributed (i.i.d.) Gaussian sources with side information available at the decoder in the form of a noisy version of the source to be coded. Our results reveal the promise of this approach: using trellis-based quantization and coset construction, the performance of the proposed approach is 2-5 dB from the Wyner-Ziv bound.
Hyperspectral imagery is usually highly correlated, in some cases within each spectral band, but in particular across neighboring frequency bands. In this paper, we propose to use distributed source coding (DSC) to ex...
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Hyperspectral imagery is usually highly correlated, in some cases within each spectral band, but in particular across neighboring frequency bands. In this paper, we propose to use distributed source coding (DSC) to exploit this correlation with an eye to a more efficient hardware implementation. The theoretical underpinnings of DSC are laid out in the pioneering work of Slepian and Wolf, and Wyner and Ziv, which provide bounds on the achievable compression when encoding correlated sources with side information available at the decoder. We apply DSC principles to hyperspectral images by encoding individual images (each image representing a spectral band) under the assumption that these bands are correlated. Using DSC tools allows us to operate in "open loop" at the encoder, so that encoding a band does not require having access to decoded versions of (spectrally) neighboring bands. We first compute the parameters of a linear predictor to estimate the current spectral band from a neighboring one, and estimate the correlation between these two bands (after prediction). Then a wavelet transform is applied and a bit-plane representation is used for the resulting wavelet coefficients. We observe that in typical hyperspectral images, bit-planes of same frequency and significance located in neighboring spectral bands are correlated. We exploit this correlation by using low-density parity-check (LDPC)-based Slepian-Wolf codes. The code rates are chosen based on the estimated correlation. We demonstrate that set partitioning of wavelet coefficients, such as that introduced in the popular SPIHT algorithm, can be combined with our proposed DSC techniques so that coefficient significance information is sent independently for all spectral bands, while sign and refinement bits can be coded using DSC. Our proposed scheme is appealing for hardware implementation as it is easy to parallelize and has modest memory requirements. In addition to these implementation advantages, our schem
Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf codin...
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Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf coding (or lossless sourcecoding with side information at the decoder). Our main novelty is to use the base layer of a standard scalable video coder (e.g., MPEG-4/H.26L FGS or H.263+) as the decoder side information and perform layered WZC for quality enhancement. Similar to FGS coding, there is no performance difference between layered and monolithic WZC when the enhancement bitstream is generated in our proposed coder. Using an H.26L coded version as the base layer, experiments indicate that WZC gives slightly worse performance than FGS coding when the channel (for both the base and enhancement layers) is noiseless. However, when the channel is noisy, extensive simulations of video transmission over wireless networks conforming to the CDMA2000 1X standard show that H.26L base layer coding plus Wyner-Ziv enhancement layer coding are more robust against channel errors than H.26L FGS coding. These results demonstrate that layered Wyner-Ziv video coding is a promising new technique for video streaming over wireless networks.
In this paper, we address the problem of distributedcoding of three correlated memoryless binary and Gaussian sources using punctured Turbo Codes. We first revisit the problem of coding with side information of two b...
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In this paper, we address the problem of distributedcoding of three correlated memoryless binary and Gaussian sources using punctured Turbo Codes. We first revisit the problem of coding with side information of two binary and Gaussian sources. The problem of coding continuous-valued Gaussian sources with partial side information is considered. The impact of the distortion induced by the quantization of the side information on the performance of the coding system is analyzed. Theoretical bounds as well as practical coding performances of sourcecoding with partial side information are given. This leads to the derivation of appropriate settings for the problem of distributedcoding of three sources. Rate bounds for the problems of coding with side information of three binary or Gaussian sources are derived. Practical solutions based on punctured Turbo Codes are provided. Simulation results are presented and analyzed for different amounts of correlation. (c) 2006 Elsevier B.V. All rights reserved.
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