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Proceedings Paper

Minimization of color halftone texture visibility using three-dimensional error diffusion neural network
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Paper Abstract

Previously we have shown that error diffusion neural networks (EDNs) find local minima of frequency-weighted error between a binary halftone output and corresponding smoothly varying input, an ideal framework for solving halftone problems. An extension of our work to color halftoning employs a three dimensional (3D) interconnect scheme. We cast color halftoning as four related sub-problems: the first three are to compute good binary halftones for each primary color and the fourth is to simultaneously minimize frequency-weighted error in the luminosity of the composite result. We have showed that an EDN with a 3D interconnect scheme can solve all four problems in parallel. This paper shows that our 3D EDN algorithm not only shapes the error to frequencies to which the Human Visual System (HVS) is least sensitive but also shapes the error in colors to which the HVS is least sensitive. The correlation among the color planes by luminosity reduces the formation of high contrast pixels, such as black and white pixels that often constitute color noise, resulting in a smoother and more homogeneous appearance in a halftone image and a closer resemblance to the continuous tone image. The texture visibility of color halftone patterns is evaluated in two ways: (1) by computing the radially averaged power spectrum (2) by computing the visual cost function.

Paper Details

Date Published: 10 February 2009
PDF: 10 pages
Proc. SPIE 7245, Image Processing: Algorithms and Systems VII, 724513 (10 February 2009); doi: 10.1117/12.805481
Show Author Affiliations
Wenli Huang, U.S. Military Academy (United States)
Eugene K. Ressler, U.S. Military Academy (United States)
Barry L. Shoop, U.S. Military Academy (United States)

Published in SPIE Proceedings Vol. 7245:
Image Processing: Algorithms and Systems VII
Nasser M. Nasrabadi; Jaakko T. Astola; Karen O. Egiazarian; Syed A. Rizvi, Editor(s)

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