Distributed source coding without Slepian-Wolf compression
Yang Yang, Zixiang Xiong
Abstract
Yang Yang, Zixiang Xiong
Abstract
Slepian-Wolf (SW) coding, which is concerned with separate near-lossless compression of correlated sources (with joint decoding), forms the basis of distributed source coding (DSC) and can be used to exploit the correlation among quantized sources in lossy DSC problems such as Wyner-Ziv (WZ) coding and multiterminal (MT) source coding. However, SW coding is in general lossy, especially at short block length, and practical implementation is not nearly as well understood as entropy coding. This paper studies distributed source coding without SW coding. We employ entropy coding (after quantization if necessary) at each encoder while relying on joint estimation at the decoder to exploit the source correlation. We start from the simple lossless case before giving single-letter characterizations of the rate-distortion function for WZ coding without SW compression, and achievable rate region for MT source coding without SW compression. Examples on the binary symmetric and quadratic Gaussian cases are given.
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Slepian-Wolf (SW) coding, which is concerned with separate near-lossless compression of correlated sources (with joint decoding), forms the basis of distributed source coding (DSC) and can be used to exploit the correlation among quantized sources in lossy DSC problems such as Wyner-Ziv (WZ) coding and multiterminal (MT) source coding. However, SW coding is in general lossy, especially at short block length, and practical implementation is not nearly as well understood as entropy coding. This paper studies distributed source coding without SW coding. We employ entropy coding (after quantization if necessary) at each encoder while relying on joint estimation at the decoder to exploit the source correlation. We start from the simple lossless case before giving single-letter characterizations of the rate-distortion function for WZ coding without SW compression, and achievable rate region for MT source coding without SW compression. Examples on the binary symmetric and quadratic Gaussian cases are given.
Key concepts: Tunstall coding, Context-adaptive binary arithmetic coding, Distributed source coding, Entropy encoding, Lossy compression, Shannon–Fano coding, Variable-length code, Lossless compression