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Entropy-constrained halftoning using multipath tree coding.

P W Wong1

  • 1Hewlett-Packard Co., Palo Alto, CA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1997
PubMed
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This study introduces an advanced optimization method for halftoning, enhancing image quality and compression. The new technique balances visual fidelity with efficient data storage for digital images.

Area of Science:

  • Digital Imaging
  • Computer Vision
  • Image Processing

Background:

  • Halftoning is crucial for displaying continuous-tone images on binary output devices.
  • Existing methods often face a trade-off between high image quality and compression efficiency.
  • Optimization-based approaches offer potential for improved halftoning performance.

Purpose of the Study:

  • To develop an optimization-based halftoning method that improves both image quality and compression.
  • To introduce a novel distortion criterion combining frequency-weighted mean square error (MSE) and pixel distribution.
  • To integrate an entropy constraint for balancing visual fidelity and compression.

Main Methods:

  • Defined a mixture distortion criterion incorporating frequency-weighted MSE and minority pixel distances.

Related Experiment Videos

  • Employed a tree-coding approach with the ML-algorithm to minimize the distortion criterion.
  • Introduced an entropy constraint into the tree-coding cost function.

    • Main Results:

    • The proposed method generates high-quality halftones.
    • Initial optimization without constraints resulted in halftones not amenable to lossless compression.
    • Incorporating the entropy constraint achieved an optimal trade-off between image quality and compression.

    Conclusions:

    • The optimization-based halftoning method with an entropy constraint effectively balances image quality and compression.
    • This approach offers a practical solution for digital image display and storage.
    • Future work could explore further refinements of the distortion criterion and entropy constraint.