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Proceedings Paper

Digital halftoning based on color correction using neural network with uniform color samples and vector error diffusion
Author(s): Cheol-Hee Lee; Won-Hee Choi; Eung-Joo Lee; Yeong-Ho Ha
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Paper Abstract

This paper proposes a uniform color sample selection and color halftoning method based on color correction using neural network with a set of uniform color samples and selective vector error diffusion for enhancing color reproduction on a printer. In order to generate uniform color samples in CIELAB color space, a set of uniformly populated color samples in a CIELAB printer gamut and monitor gamut are calculated by LBG (Linde, Buzo, Gray) quantization algorithm. Then, the corresponding device- dependent values of CMY and RGB are estimated by a trained NN, which was temporally trained by a set of uniform samples in the device-dependent spaces.

Paper Details

Date Published: 21 December 1999
PDF: 8 pages
Proc. SPIE 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V, (21 December 1999); doi: 10.1117/12.373423
Show Author Affiliations
Cheol-Hee Lee, Kyungpook National Univ. (South Korea)
Won-Hee Choi, Kyungpook National Univ. (South Korea)
Eung-Joo Lee, Tongmyong Univ. of Information Technology (South Korea)
Yeong-Ho Ha, Kyungpook National Univ. (South Korea)


Published in SPIE Proceedings Vol. 3963:
Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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