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Proceedings Paper

Empirical assessment of selected color-quantizing algorithms
Author(s): Susy S. Chan; Rosalee Nerheim-Wolfe
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Paper Abstract

We develop an empirical approach for evaluating the performance of color-quantizing algorithms in controlled laboratory experiments. We chose a 4 X 4 X 2 factorial experimental design to examine the performance of four algorithms at four palette sizes in two arrangements. The independent variables are algorithm, palette size and arrangement, and the dependent variables are perceived color fidelity, contrast, and overall quality. Subjects observed 128 quantized images on slides. We find significant between-subject effects of palette size and algorithms on all dependent variables, and observe consistent patterns of significant palette size effects. The 16-color palette results in the poorest perceived image quality, and the 64-color palette is poorer than the 256-color palette. However, there is homogeneity in performance between 64 and 128 colors, and between 128 colors and 256 colors. The effect of algorithm is less consistent.

Paper Details

Date Published: 1 May 1994
PDF: 12 pages
Proc. SPIE 2179, Human Vision, Visual Processing, and Digital Display V, (1 May 1994); doi: 10.1117/12.172681
Show Author Affiliations
Susy S. Chan, DePaul Univ. (United States)
Rosalee Nerheim-Wolfe, DePaul Univ. (United States)

Published in SPIE Proceedings Vol. 2179:
Human Vision, Visual Processing, and Digital Display V
Bernice E. Rogowitz; Jan P. Allebach, Editor(s)

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