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Rate-Distortion Region of a Gray-Wyner Model with Side Information.

Meryem Benammar1, Abdellatif Zaidi2

  • 1Department of Electronics Optronics and Signal Processing (DEOS), Institut Superieur de l'Aéronautique et de l'Espace Supaéro (ISAE Supaéro), 31400 Toulouse, France.

Entropy (Basel, Switzerland)
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PubMed
Summary

This study characterizes the rate-distortion region for the Gray-Wyner model with side information. It analyzes common and private descriptions for successive refinement and scalable coding, offering insights into data compression strategies.

Keywords:
Gray–WynerHeegard–Bergerrate-distortionside-informationsuccessive refinement

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Area of Science:

  • Information Theory
  • Data Compression
  • Lossy Compression

Background:

  • The Gray-Wyner model addresses data compression with side information available at decoders.
  • Understanding the trade-offs between compression rates and distortion is crucial for efficient communication systems.

Purpose of the Study:

  • To establish a full single-letter characterization of the rate-distortion region for a specific Gray-Wyner model.
  • To analyze the roles of common and private descriptions and communication links in successive refinement and scalable coding.

Main Methods:

  • Derivation of a single-letter rate-distortion region for the Gray-Wyner model.
  • Specialization of the main result to Heegard-Berger models for successive refinement and scalable coding.
  • Analysis of arbitrary correlations between sources and side information.

Main Results:

  • A complete characterization of the rate-distortion region is established.
  • The study elucidates the interplay between common and private information in layered compression schemes.
  • Insights are provided into the optimal use of rate-limited links for transmitting source components and side information.

Conclusions:

  • The derived rate-distortion region offers a fundamental understanding of compression limits in the presence of side information.
  • The analysis provides valuable insights for designing efficient communication systems employing successive refinement and scalable coding.
  • The findings are further illustrated through insightful binary examples.