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Related Experiment Videos

Hierarchical partition priority wavelet image compression.

S N Efstratiadis1, D Tzovaras, M G Strintzis

  • 1Lab. of Inf. Process., Aristotelian Univ. of Thessaloniki.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1996
PubMed
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New image compression techniques enhance progressive transmission using hierarchical decomposition and advanced coding. These methods improve image fidelity and reduce data size for efficient transmission.

Area of Science:

  • Digital image processing
  • Signal processing
  • Information theory

Background:

  • Progressive image transmission requires efficient compression methods.
  • Existing techniques may not fully optimize fidelity across transmission stages.
  • Hierarchical decomposition offers potential for improved image representation.

Purpose of the Study:

  • To develop novel image compression methods for progressive transmission.
  • To enhance reproduction fidelity at each stage of transmission.
  • To improve coding efficiency using advanced algorithms.

Main Methods:

  • Hierarchical subband/wavelet decomposition with optimized filter banks.
  • Triple-state differential pulse code modulation (DPCM) and Lloyd-Max quantization.

Related Experiment Videos

  • Hierarchical partition priority coding (HPPC), predictive HPPC (PHPPC), and adaptive multiple distribution entropy coding (MDEC).

    • Main Results:

    • The proposed coder achieves high reproduction fidelity during progressive transmission.
    • HPPC and PHPPC algorithms efficiently code detail coefficients.
    • Adaptive MDEC further optimizes compression ratios by exploiting coefficient characteristics.

    Conclusions:

    • The presented image compression methods offer superior performance for progressive transmission.
    • The combination of hierarchical decomposition and advanced coding strategies is effective.
    • The techniques provide a significant advancement in image compression technology.