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Proceedings Paper

Applications of fractal analysis in the evaluation of halftoning algorithms and a fractal-based halftoning scheme
Author(s): Theophano Mitsa; Jennifer R. Alford
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Paper Abstract

Fractals are mathematical sets that model many natural phenomena and physical object such as clouds, mountains, trees, and coastlines. The principal features of fractal objects are: (1) a large degree of heterogeneity, (2) scaling similarity over many scales of observation, and (3) the lack of a well-defined (or characteristic) scale. In this paper, we investigate the applications of fractal analysis in halftoning. Specifically, we first investigate and compare the fractal properties of aperiodic constant-gray-level halftone patterns produced by error diffusion, the blue-noise mask, and white noise. Then, given that the fractal dimension of an image area can predict the perceived smoothness or roughness of this area's texture, we describe an error diffusion scheme where the error weights depend on the local fractal dimension of the gray scale image prior to halftoning. The resulting halftones have less grainy flat areas and sharper edges than standard error diffusion with perturbed weights. This can be attributed to incorporation of texture information in the ehalftoning scheme that distributes the halftoning error in proportion to local texture roughness and therefore diffuses it in the areas where it is least visible.

Paper Details

Date Published: 1 May 1994
PDF: 12 pages
Proc. SPIE 2179, Human Vision, Visual Processing, and Digital Display V, (1 May 1994); doi: 10.1117/12.172671
Show Author Affiliations
Theophano Mitsa, Univ. of Iowa (United States)
Jennifer R. Alford, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 2179:
Human Vision, Visual Processing, and Digital Display V
Bernice E. Rogowitz; Jan P. Allebach, Editor(s)

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