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Proceedings Paper

Variations on error diffusion: retrospectives and future trends
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Paper Abstract

Grayscale error diffusion introduces nonlinear distortion (directional artifacts and false textures), linear distortion (sharpening), and additive noise. Since error diffusion is 2-D sigma-delta modulation (Anastassiou, 1989), Kite et al. linearize error diffusion by replacing the thresholding quantizer with a scalar gain plus additive noise. Sharpening is proportional to the scalar gain. Kite et al. derive the sharpness control parameter value in threshold modulation (Eschbach and Knox, 1991) to compensate linear distortion. These unsharpened halftones are particularly useful in perceptually weighted SNR measures. False textures at mid-gray (Fan and Eschbach, 1994) are due to limit cycles, which can be broken up by using a deterministic bit flipping quantizer (Damera-Venkata and Evans, 2001). We review other variations on grayscale error diffusion to reduce false textures in shadow and highlight regions, including green noise halftoning Levien, 1993) and tone-dependent error diffusion (Li and Allebach, 2002). We then discuss color error diffusion in several forms: color plane separable (Kolpatzik and Bouman, 1992); vector quantization (Shaked et al. 1996); green noise extensions (Lau et al. 2000); and matrix-valued error filters (Damera-Venkata and Evans, 2001). We conclude with open research problems.

Paper Details

Date Published: 13 January 2003
PDF: 19 pages
Proc. SPIE 5008, Color Imaging VIII: Processing, Hardcopy, and Applications, (13 January 2003); doi: 10.1117/12.481450
Show Author Affiliations
Brian L. Evans, Univ. of Texas at Austin (United States)
Vishal Monga, Univ. of Texas at Austin (United States)
Niranjan Damera-Venkata, Hewlett-Packard Labs. (United States)


Published in SPIE Proceedings Vol. 5008:
Color Imaging VIII: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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