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Tone-dependent error diffusion.

Pingshan Li1, Jan P Allebach

  • 1School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907-1285 USA. pingshan@usrl.sony.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|September 21, 2004
PubMed
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This study introduces an improved error diffusion halftoning algorithm. It optimizes filter weights and thresholds using a human visual model, reducing artifacts and improving image quality.

Area of Science:

  • Computer Vision
  • Image Processing
  • Digital Halftoning

Background:

  • Error diffusion halftoning is crucial for converting continuous-tone images to bilevel images.
  • Existing algorithms often suffer from artifacts like edge effects and 'worms'.

Purpose of the Study:

  • To enhance error diffusion halftoning algorithms for improved image quality.
  • To reduce visual artifacts such as edge effects and 'worms' in halftoned images.

Main Methods:

  • Developed an algorithm with input pixel-value-dependent filter weights and quantizer thresholds.
  • Optimized weights and thresholds using a human visual system model.
  • Introduced a tone-dependent threshold to mitigate edge effects.
  • Proposed a parallel scan error diffusion system with variable weight locations to reduce 'worms'.

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Main Results:

  • The enhanced algorithm demonstrates reduced edge effects and start-up delay.
  • Variable weight locations in the parallel scan system effectively minimize 'worms'.

Conclusions:

  • The proposed algorithm significantly improves the quality of error diffusion halftoning.
  • The human visual system model-based optimization and specific artifact reduction techniques offer a robust solution for digital halftoning.