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Proceedings Paper

Selection of small color palette for color image quantization
Author(s): Wing Ki Chau; S. K. M. Wong; Xuedong Yang; Shijie J. Wan
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Paper Abstract

Two issues are involved in color image quantization: color palette selection and color mapping. A common practice for color palette selection is to minimize the color distortion for each pixel (the median-cut, the variance-based and the k-means algorithms). After the color palette has been chosen, a quantized image may be generated by mapping the original color of each pixel onto its nearest color in the color palette. Such an approach can usually produce quantized images of high quality with 128 or more colors. For 32 - 64 colors, the quality of the quantized images is often acceptable with the aid of dithering techniques in the color mapping process. For 8 - 16 color, however, the above statistical method for color selection becomes no longer suitable because of the great reduction of color gamut. In order to preserve the color gamut of the original image, one may want to select the colors in such a way that the convex hull formed by these colors in the RGB color space encloses most colors of the original image. Quantized images generated in such a geometrical way usually preserve a lot of image details, but may contain too much high frequency noises. This paper presents an effective algorithm for the selection of very small color palette by combining the strengths of the above statistical and geometrical approaches. We demonstrate that with the new method images of high quality can be produced by using only 4 to 8 colors.

Paper Details

Date Published: 19 May 1992
PDF: 8 pages
Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); doi: 10.1117/12.58339
Show Author Affiliations
Wing Ki Chau, Univ. of Regina (Canada)
S. K. M. Wong, Univ. of Regina (Canada)
Xuedong Yang, Univ. of Regina (Canada)
Shijie J. Wan, Univ. of Regina (Canada)


Published in SPIE Proceedings Vol. 1657:
Image Processing Algorithms and Techniques III
James R. Sullivan; Benjamin M. Dawson; Majid Rabbani, Editor(s)

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