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Proceedings Paper

Two-stage color palettization for error diffusion
Author(s): Niloy J. Mitra; Maya R. Gupta
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Paper Abstract

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 M 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.

Paper Details

Date Published: 30 May 2002
PDF: 11 pages
Proc. SPIE 4662, Human Vision and Electronic Imaging VII, (30 May 2002); doi: 10.1117/12.469516
Show Author Affiliations
Niloy J. Mitra, Stanford Univ. (United States)
Maya R. Gupta, Stanford Univ. (United States)


Published in SPIE Proceedings Vol. 4662:
Human Vision and Electronic Imaging VII
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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