Vector quantization by lazy pairwise nearest neighbor method

Timo Kaukoranta; Pasi Franti; Olli Nevalainen

doi:10.1117/1.602251

1 November 1999 Vector quantization by lazy pairwise nearest neighbor method

Timo Kaukoranta, Pasi Franti, Olli Nevalainen

Optical Engineering, Vol. 38, Issue 11, (November 1999). https://doi.org/10.1117/1.602251

The pairwise nearest neighbor (PNN) algorithm is a well- known method for the codebook construction in vector quantization and for the clustering of data sets. The algorithm has a simple structure and it provides high quality solutions. A drawback of the method is the large running time of the original (exact) implementation. We prove the monotony of the merge costs of the pNn. The monotony property is utilized to speed up an existing PNN variant. The idea is to postpone a number of distance calculations. In this way, we can reduce the computation by about 35% while preserving the exactness of the PNN.

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Timo Kaukoranta, Pasi Franti, and Olli Nevalainen "Vector quantization by lazy pairwise nearest neighbor method," Optical Engineering 38(11), (1 November 1999). https://doi.org/10.1117/1.602251

Published: 1 November 1999

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