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Arithmetic Coding

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Gabriella Olmo – One of the best experts on this subject based on the ideXlab platform.

  • distributed Arithmetic Coding for the slepian wolf problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    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 ldquodistributed Arithmetic Coding,rdquo 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 small 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.

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  • Distributed Arithmetic Coding for the Slepian–Wolf Problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    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 ldquodistributed Arithmetic Coding,rdquo 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 small 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.

    Free Register to Access Article

  • Distributed Arithmetic Coding for the Asymmetric Slepian-Wolf problem
    arXiv: Information Theory, 2007
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    Distributed source Coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, termed “distributed Arithmetic Coding“, which exploits the fact that Arithmetic codes are good source as well as channel codes. In particular, 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 Slepian-Wolf coders, especially its good performance at small block lengths, and the ability to incorporate arbitrary source models in the enCoding process, e.g. context-based statistical models. We have compared the performance of distributed Arithmetic Coding with turbo codes and low-density parity-check codes, and found that the proposed approach has very competitive performance.

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Marco Grangetto – One of the best experts on this subject based on the ideXlab platform.

  • distributed Arithmetic Coding for the slepian wolf problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    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 ldquodistributed Arithmetic Coding,rdquo 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 small 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.

    Free Register to Access Article

  • Distributed Arithmetic Coding for the Slepian–Wolf Problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    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 ldquodistributed Arithmetic Coding,rdquo 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 small 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.

    Free Register to Access Article

  • Distributed Arithmetic Coding for the Asymmetric Slepian-Wolf problem
    arXiv: Information Theory, 2007
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    Distributed source Coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, termed “distributed Arithmetic Coding“, which exploits the fact that Arithmetic codes are good source as well as channel codes. In particular, 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 Slepian-Wolf coders, especially its good performance at small block lengths, and the ability to incorporate arbitrary source models in the enCoding process, e.g. context-based statistical models. We have compared the performance of distributed Arithmetic Coding with turbo codes and low-density parity-check codes, and found that the proposed approach has very competitive performance.

    Free Register to Access Article

Enrico Magli – One of the best experts on this subject based on the ideXlab platform.

  • distributed Arithmetic Coding for the slepian wolf problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    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 ldquodistributed Arithmetic Coding,rdquo 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 small 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.

    Free Register to Access Article

  • Distributed Arithmetic Coding for the Slepian–Wolf Problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    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 ldquodistributed Arithmetic Coding,rdquo 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 small 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.

    Free Register to Access Article

  • Distributed Arithmetic Coding for the Asymmetric Slepian-Wolf problem
    arXiv: Information Theory, 2007
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo

    Abstract:

    Distributed source Coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, termed “distributed Arithmetic Coding“, which exploits the fact that Arithmetic codes are good source as well as channel codes. In particular, 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 Slepian-Wolf coders, especially its good performance at small block lengths, and the ability to incorporate arbitrary source models in the enCoding process, e.g. context-based statistical models. We have compared the performance of distributed Arithmetic Coding with turbo codes and low-density parity-check codes, and found that the proposed approach has very competitive performance.

    Free Register to Access Article