ACM Transactions on Information Systems (TOIS)
Source and Channel Coding: An Algorithmic Approach
Source and Channel Coding: An Algorithmic Approach
DCC '03 Proceedings of the Conference on Data Compression
Linear-Time Construction of Optimal Context Trees
DCC '98 Proceedings of the Conference on Data Compression
Approaching the Slepian-Wolf boundary using practical channel codes
Signal Processing - Special section: Distributed source coding
A general and optimal framework to achieve the entire rate region for Slepian-Wolf coding
Signal Processing - Special section: Distributed source coding
Rate-adaptive codes for distributed source coding
Signal Processing - Special section: Distributed source coding
Efficient wavelet-based predictive Slepian-Wolf coding for hyperspectral imagery
Signal Processing - Special section: Distributed source coding
Distributed source coding techniques for lossless compression of hyperspectral images
EURASIP Journal on Applied Signal Processing
Successive refinement for the Wyner-Ziv problem and layered code design
IEEE Transactions on Signal Processing - Part II
Wyner-Ziv coding of video: an error-resilient compression framework
IEEE Transactions on Multimedia
The rate loss in the Wyner-Ziv problem
IEEE Transactions on Information Theory - Part 2
Efficient encoding of low-density parity-check codes
IEEE Transactions on Information Theory
On zero-error source coding with decoder side information
IEEE Transactions on Information Theory
Lossless and near-lossless source coding for multiple access networks
IEEE Transactions on Information Theory
Distributed source coding using syndromes (DISCUS): design and construction
IEEE Transactions on Information Theory
Duality between source coding and channel coding and its extension to the side information case
IEEE Transactions on Information Theory
Generalized coset codes for distributed binning
IEEE Transactions on Information Theory
On code design for the Slepian-Wolf problem and lossless multiterminal networks
IEEE Transactions on Information Theory
Joint turbo decoding and estimation of hidden Markov sources
IEEE Journal on Selected Areas in Communications
Layered Wyner–Ziv Video Coding
IEEE Transactions on Image Processing
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Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named "distributed arithmetic coding?" which extends arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary arithmetic coder for the Slepian-Wolf coding problem, along with a joint decoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed arithmetic coding provides several advantages over existing Slepian-Wolf coders, especially good performance at smaIl block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical arithmetic coder. We have compared the performance of distributed arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.