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Optical Engineering

Vector quantization by lazy pairwise nearest neighbor method
Author(s): Timo Kaukoranta; Pasi Franti; Olli Nevalainen
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Paper Abstract

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.

Paper Details

Date Published: 1 November 1999
PDF: 7 pages
Opt. Eng. 38(11) doi: 10.1117/1.602251
Published in: Optical Engineering Volume 38, Issue 11
Show Author Affiliations
Timo Kaukoranta, Univ. of Turku (Finland)
Pasi Franti, Univ. of Joensuu (Finland)
Olli Nevalainen, Univ. of Turku (Finland)


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