IEEE Transactions on Image Processing,
vol. 10, no. 10, pp. 1552-1565, Oct. 2001.
Design and Analysis of Vector Color Error Diffusion Halftoning Systems
Damera-Venkata (1) and
Brian L. Evans (2)
(1) Halftoning and Image Processing Group,
1501 Page Mill Road,
Palo Alto, CA 94304
(2) Department of Electrical and Computer Engineering,
Engineering Science Building,
The University of Texas at Austin,
Austin, TX 78712-1084 USA
Draft of Paper for Press -
Vector Filter Design Matlab Code
Toolbox for Matlab -
at UT Austin
Traditional error diffusion halftoning is a high quality method for
producing binary images from digital grayscale images.
Error diffusion shapes the quantization noise power into the
high frequency regions where the human eye is the least sensitive.
Error diffusion may be extended to color images by using error
filters with matrix-valued coefficients to take into account the
correlation among color planes.
For vector color error diffusion, we propose three contributions.
First, we analyze vector color error diffusion based on a new matrix
gain model for the quantizer, which linearizes vector error diffusion.
The model predicts key characteristics of color error diffusion,
esp. image sharpening and noise shaping.
The proposed model includes linear gain models for the quantizer
by Ardalan and Paulos and by Kite, Evans, and Bovik as special cases.
Second, based on our model, we optimize the noise shaping behavior of
color error diffusion by designing error filters that are optimum
with respect to any given linear spatially-invariant model of the
human visual system.
Our approach allows the error filter to have matrix-valued coefficients
and diffuse quantization error across color channels in an opponent color
Thus, the noise is shaped into frequency regions of reduced human
To obtain the optimal filter, we derive a matrix version of the
Yule-Walker equations which we solve by using a gradient descent algorithm.
Finally, we show that the vector error filter has a parallel
implementation as a polyphase filterbank.
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