Input-level-dependent approach to color error diffusion

High-performance architecture for color error diffusion

10.1117/12.477498 ◽

2003 ◽

Author(s):

Christopher R. Brown ◽

Andreas E. Savakis

Keyword(s):

High Performance ◽

Error Diffusion ◽

Color Error

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15.3: Color Error Diffusion: Accurate Luminance from Coarsely Quantized Displays

SID Symposium Digest of Technical Papers ◽

10.1889/1.1831834 ◽

2001 ◽

Vol 32 (1) ◽

pp. 214

Author(s):

Michiel A. Klompenhouwer ◽

Gerard de Haan

Keyword(s):

Error Diffusion ◽

Color Error

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Color error-diffusion halftoning what differentiates it from grayscale error diffusion?

IEEE Signal Processing Magazine ◽

10.1109/msp.2003.1215231 ◽

2003 ◽

Vol 20 (4) ◽

pp. 51-58 ◽

Cited By ~ 18

Author(s):

N. Damera-Venkata ◽

B.L. Evans ◽

V. Monga

Keyword(s):

Error Diffusion ◽

Color Error

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Neugebauer Models for Color Error Diffusion Halftoning

Journal of Imaging ◽

10.3390/jimaging6040023 ◽

2020 ◽

Vol 6 (4) ◽

pp. 23

Author(s):

Kaiming Wu ◽

Kohei Inoue ◽

Kenji Hara

Keyword(s):

Natural Extension ◽

Design Criterion ◽

Diffusion Method ◽

Error Diffusion ◽

Blue Color ◽

Color Design ◽

Color Version ◽

Model Based ◽

Color Error ◽

Better Than

In this paper, we propose a method for halftoning color images based on an error diffusion technique, a color design criterion and Neugebauer models for expressing colors. For a natural extension of the conventional method for grayscale error diffusion to its color version, we first reformulate grayscale error diffusion with a one-dimensional Neugebauer model. Then we increase the dimension of the model to derive a color error diffusion method based on a three-dimensional Neugebauer model in RGB (red, green and blue) color space. Moreover, we propose a sparse Neugebauer model based on a color design criterion, or the minimal brightness variation criterion (MBVC), from which we derive a sparse Neugebauer model-based error diffusion method. Experimental results show that color halftone images produced by the proposed methods preserve the color contents in original continuous-tone images better than that by conventional color error diffusion methods. We also demonstrate that the proposed sparse method reduce halftone noise better than the state-of-the-art method based on MBVC.

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