Many digital display devices allow only a limited number of colors to be displayed
concurrently. Digitized color images typically contain several hundred to several
thousand different colors. If these color images are to be viewed on displays with a
limited color palette, the number of colors used to represent the image must be reduced
to satisfy the display limits. This process is known as color quantization and is a special
case of vector quantization. It has been shown that images containing large numbers of
colors can be quantized to a very small color palette with little degradation in visual
quality. This thesis presents a new algorithm, based on Heckbert's original median cut
procedure, for creating near-original quality images using a small color palette. We have
found that slight changes to Heckbert's original algorithm yield dramatic improvements
in quantizer performance. The color quantization problem is considered in two parts:
the selection of the optimal color palette, and the optimal mapping of each image pixel to
a color from the palette. The method to be described is an image dependent quantizer in
ROB color space. Resulting image quality is measured both subjectively and with a
squared error metric.
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