Digital halftoning based on color correction using neural network with uniform color samples and vector error diffusion

Cheol-Hee Lee; Won-Hee Choi; Eung-Joo Lee; Yeong-Ho Ha

doi:10.1117/12.373423

21 December 1999 Digital halftoning based on color correction using neural network with uniform color samples and vector error diffusion

Cheol-Hee Lee, Won-Hee Choi, Eung-Joo Lee, Yeong-Ho Ha

Author Affiliations +

Proceedings Volume 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V; (1999) https://doi.org/10.1117/12.373423
Event: Electronic Imaging, 2000, San Jose, CA, United States

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.

Citation Download Citation

Cheol-Hee Lee, Won-Hee Choi, Eung-Joo Lee, and Yeong-Ho Ha "Digital halftoning based on color correction using neural network with uniform color samples and vector error diffusion", Proc. SPIE 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V, (21 December 1999); https://doi.org/10.1117/12.373423

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