Reinstating Floyd-Steinberg: Improved Metrics for Quality Assessment of Error Diffusion Algorithms

  • Sam Hocevar
  • Gary Niger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5099)

Abstract

In this contribution we introduce a little-known property of error diffusion halftoning algorithms which we call error diffusion displacement. By accounting for the inherent sub-pixel displacement caused by the error propagation, we correct an important flaw in most metrics used to assess the quality of resulting halftones. We find these metrics to usually highly underestimate the quality of error diffusion in comparison to more modern algorithms such as direct binary search. Using empirical observation, we give a method for creating computationally efficient, image-independent, model-based metrics for this quality assessment. Finally, we use the properties of error diffusion displacement to justify Floyd and Steinberg’s well-known choice of algorithm coefficients.

Keywords

halftoning error diffusion image quality human visual system color quantization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Sam Hocevar
    • 1
  • Gary Niger
    • 2
  1. 1.Laboratoire d’Imagerie Bureautique et de Conception Artistique ParisFrance
  2. 2. Tarzana

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