Title :
A novel full-search vector quantization algorithm based on the law of cosines
Author :
Mielikainen, Jarno
Author_Institution :
Dept. of Inf. Technol., Lappeenranta Univ. of Technol., Finland
fDate :
6/1/2002 12:00:00 AM
Abstract :
Vector quantization (VQ) 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. Using law of cosines this letter presents a simple improved method for nearest-neighbor search in GLA. Experiments show that the proposed algorithm outperforms the traditional GLA.
Keywords :
data compression; image coding; search problems; vector quantisation; GLA; VQ; cosines law; data compression; full-search vector quantization algorithm; generalized Lloyd algorithm; image coding; multispectral images; nearest-neighbor search; signal processing; vector quantizer design; Algorithm design and analysis; Computational complexity; Data compression; Decoding; Encoding; Iterative algorithms; Nearest neighbor searches; Signal processing algorithms; Table lookup; Vector quantization;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2002.800507