An improved algorithm for vector quantizer design

Vector quantization is an essential tool in signal processing. Although many algorithms for vector quantizer design have been developed, the classical generalized Lloyd algorithm (GLA) is still widely used, mainly for its simplicity and relatively good performance. Recently, Lee et al. (see IEEE Sig...

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Published in:IEEE signal processing letters 2000-09, Vol.7 (9), p.250-252
Main Authors: Veprek, P., Bradley, A.B.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Clustering algorithms
Code standards
Counters
Data compression
Distortion
Mathematical analysis
Nearest neighbor searches
Quantization
Signal processing
Signal processing algorithms
Terminology
Training data
Vector quantization
Vectors (mathematics)
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description Vector quantization is an essential tool in signal processing. Although many algorithms for vector quantizer design have been developed, the classical generalized Lloyd algorithm (GLA) is still widely used, mainly for its simplicity and relatively good performance. Recently, Lee et al. (see IEEE Signal Processing Lett., vol.4, p.2-4, Jan. 1997) proposed an intuitive modification of the K-means algorithm (MKMA). In this letter, we propose an improved algorithm that uses the standard GLA embedded in a codevector reassignment loop. The algorithm achieves better performance by targeting specifically those sections of the codebook that contribute most to the overall reconstructed signal distortion. Simulations show that the proposed algorithm outperforms both the traditional GLA and MKMA in a variety of scenarios.
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subjects Algorithm design and analysis
Algorithms
Clustering algorithms
Code standards
Counters
Data compression
Distortion
Mathematical analysis
Nearest neighbor searches
Quantization
Signal processing
Signal processing algorithms
Terminology
Training data
Vector quantization
Vectors (mathematics)
title An improved algorithm for vector quantizer design
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