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A new vector quantization clustering algorithm

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1 Author(s)
W. H. Equitz ; IBM Almaden Res. Center, San Jose, CA, USA

The pairwise nearest neighbor (PNN) algorithm is presented as an alternative to the Linde-Buzo-Gray (1980, LBG) (generalized Lloyd, 1982) algorithm for vector quantization clustering. The PNN algorithm derives a vector quantization codebook in a diminishingly small fraction of the time previously required, without sacrificing performance. In addition, the time needed to generate a codebook grows only O(N log N ) in training set size and is independent of the number of code words desired. Using this method, one can either minimize the number of code words needed subject to a maximum rate. The PNN algorithm can be used with squared error and weighted squared error distortion measure. Simulations on a variety of images encoded at 1/2 b/pixel indicate that PNN codebooks can be developed in roughly 5% of the time required by the LBG algorithm

Published in:

IEEE Transactions on Acoustics, Speech, and Signal Processing  (Volume:37 ,  Issue: 10 )