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Adaptive threshold modulation for error diffusion halftoning.

N Damera-Venkata1, B L Evans

  • 1The University of Texas, Austin, TX 78712, USA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
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This study introduces an adaptive threshold modulation framework to enhance digital image halftoning quality. It optimizes error diffusion parameters, reducing artifacts and improving edge enhancement and green noise halftoning.

Area of Science:

  • Digital Image Processing
  • Computer Vision
  • Signal Processing

Background:

  • Grayscale digital image halftoning quantizes pixels to one bit.
  • Error diffusion halftoning introduces nonlinear (directional artifacts) and linear (sharpening) distortions, plus additive noise.
  • Threshold modulation can reduce specific distortions but requires optimization.

Purpose of the Study:

  • To present an adaptive threshold modulation framework for improving halftone quality.
  • To optimize error diffusion parameters in a least squares sense.
  • To derive adaptive algorithms for edge enhancement and green noise halftoning.

Main Methods:

  • Developed an adaptive threshold modulation framework that implicitly models quantizers.
  • Applied a least squares optimization approach to error diffusion parameters.

Related Experiment Videos

  • Derived specific algorithms for edge enhancement (minimizing linear distortion, breaking directional artifacts) and green noise halftoning (optimizing hysteresis coefficients).

    • Main Results:

    • The framework successfully optimizes error diffusion parameters for improved halftone quality.
    • Adaptive algorithms were derived for targeted improvements in edge enhancement and green noise halftoning.
    • Demonstrated the ability to control sharpening and reduce directional artifacts.

    Conclusions:

    • The adaptive threshold modulation framework offers a flexible approach to enhance digital image halftoning.
    • Optimizing error diffusion parameters can effectively mitigate common distortions.
    • The derived algorithms provide practical solutions for specific halftoning quality improvements.