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Mutual information-based analysis of JPEG2000 contexts.

Zhen Liu1, Lina J Karam

  • 1Qualcomm, Inc., San Diego, CA 92121-1714, USA. zhenl@qualcomm.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|April 14, 2005
PubMed
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This study analyzes JPEG2000 contexts for image compression. Researchers found that context classification can be optimized using mutual information, potentially reducing the number of contexts without impacting coding performance.

Area of Science:

  • Digital image and video compression
  • Information theory
  • Data compression algorithms

Background:

  • Context-based arithmetic coding is crucial for image and video compression standards like JPEG2000.
  • Mutual information quantifies the relationship between contexts and encoded data, directly impacting compression efficiency.

Purpose of the Study:

  • To analyze the contexts used in JPEG2000 using mutual information.
  • To determine optimal context classification schemes for improved compression performance.
  • To investigate the possibility of reducing the number of contexts in JPEG2000 without performance loss.

Main Methods:

  • Analysis of context combination effects on mutual information.
  • Application of Stirling numbers of the second kind to enumerate context classification schemes.

Related Experiment Videos

  • Utilizing a modified generalized Lloyd algorithm with relative entropy for optimal classification.
  • Employing dynamic programming to reduce search complexity for binary arithmetic coding.

    • Main Results:

    • Mutual information decreases when combining contexts unless their conditional probability distributions are identical.
    • The JPEG2000 contexts effectively capture correlations in wavelet coefficients.
    • Optimal context classification schemes can be found efficiently, avoiding exhaustive search.
    • A reduction in the number of contexts is achievable without compromising coding performance.

    Conclusions:

    • The study provides a method for optimizing context classification in arithmetic coding.
    • JPEG2000's context selection is effective but can be refined for efficiency.
    • Reduced context usage is feasible, offering potential benefits for compression standards.