Kohonen Maps Applied to Fast Image Vector Quantization

Vector Quantization (VQ) is a powerful technique for image compression but its coding complexity may be an important drawback. Self-Organizing Maps (SOM) are well suited for topologically ordered codebook design. We propose to use that topology for reducing image coding time. Using inter-block correlations, the nearest neighbor search is restricted to the neighborhood of the precedingly used code vector instead of the entire codebook. We obtained a reduction of up to 84% in the coding time compared to full search.

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