Two-stage color palettization for error diffusion.
In: Rogowitz, BE and Pappas, TN, (eds.)
HUMAN VISION AND ELECTRONIC IMAGING VII.
(pp. 207 - 217).
SPIE-INT SOC OPTICAL ENGINEERING
Image-adaptive color palettization chooses a decreased number of colors to represent an image. Palettization is one way to decrease storage and memory requirements for low-end displays. Palettization is generally approached as a clustering problem, where one attempts to find the k palette colors that minimize the average distortion for all the colors in an image. This would be the optimal approach if the image was to be displayed with each pixel quantized to the closest palette color. However, to improve the image quality the palettization may be followed by error diffusion. In this work, we propose a two-stage palettization where the first stage finds some m << k clusters, and the second stage chooses palette points that cover the spread of each of the 1 clusters. After error diffusion, this method leads to better image quality at less computational cost and with faster display speed than full k-means palettization.
|Title:||Two-stage color palettization for error diffusion|
|Event:||Conference on Human Vision and Electronic Imaging VII|
|Location:||SAN JOSE, CA|
|Dates:||2002-01-21 - 2002-01-24|
|Keywords:||color palettization, color clustering, multi-level halftoning|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
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