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Region adaptive subband image coding.

O J Kwon1, R Chellappa

  • 1Media Laboratory, Samsung Data Systems Co, Ltd., Seoul 135-080, Korea.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 16, 2008
PubMed
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This study introduces a region adaptive subband image coding scheme. It optimizes image compression by analyzing subband properties, achieving good quality at low bit rates.

Area of Science:

  • Digital image processing
  • Signal processing
  • Information theory

Background:

  • Subband image coding exploits statistical properties of image subbands for compression.
  • Understanding energy distribution in subbands, especially around edges, is crucial for efficient coding.

Purpose of the Study:

  • To develop a region adaptive subband image coding scheme.
  • To analyze energy packing properties and edge orientation effects in subband decomposed images.
  • To determine the optimal subband decomposition for image coding.

Main Methods:

  • Analysis of energy packing properties using a unit step function as input.
  • Extraction of region-adaptive features within subbands.
  • Application of adaptive entropy-constrained quantizers assuming a generalized Gaussian distribution.

Related Experiment Videos

  • Investigation of optimal subband decomposition strategies.

    • Main Results:

    • Identified energy packing towards lower frequency subbands and dependency on edge orientation.
    • Demonstrated negligible visual degradation at 1.0 bit per pel (b/pel).
    • Achieved reasonable image quality at bit rates as low as 0.25 b/pel.

    Conclusions:

    • The proposed region adaptive scheme effectively utilizes subband statistical properties for image compression.
    • The method allows for high-quality image reconstruction at very low bit rates.
    • Optimal subband decomposition can significantly enhance coding efficiency.