Constrained quantization algorithm for color images

In this paper, we discuss two kinds of VQ algorithms. One is based on minimizing the total variance and the other is based on minimizing the maximum deviation. The algorithms of the first kind better reflect the overall fit, but may discount large, but highly localized, deviations. Those of the second kind provide absolute distance bounds that are a useful error guarantee, but may be overly sensitive to any noise that might be present in the original models. A new algorithm, combining the two criteria, is presented in this paper. It not only improves the total variance, but also provides a useful maximum error guarantee. The experiments indicate the new quantizer is a better choice in some practical operations.

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