Presented at the 1997 IEEE International Conference on Image Processing

Digital Image Halftoning As 2-D Delta-Sigma Modulation

Thomas D. Kite (1), Brian L. Evans (1), Alan C. Bovik (1), and Terry Sculley (2)

(1) Department of Electrical and Computer Engineering, Engineering Science Building, The University of Texas at Austin, Austin, TX 78712-1084 USA
tomk@audioprecision.com - bevans@ece.utexas.edu - bovik@ece.utexas.edu

(2) ESS Technology, Inc., Austin, TX 78746 USA
terry_sculley@yahoo.com

Paper - Poster

Halftoning Toolbox for Matlab - Halftoning Research at UT Austin

Abstract

The error diffusion algorithm for digital halftoning is equivalent in form to a noise-shaping feedback coder, a class of delta-sigma modulator. The white noise assumption of the quantizer error is known to be false; in fact, the quantizer error is seen to be highly correlated with the input image. To account for this correlation, we use a gain model for the quantizer. This model accurately predicts the edge sharpening and noise shaping caused by all error diffusion schemes. It also permits an extension of error diffusion to oversampled imagery.

Last Updated 11/07/04.