High‐quality initial codebook design method of vector quantisation using grouping strategy
Author(s) -
Ma Xiaoxiao,
Pan Zhibin,
Li Yang,
Fang Jie
Publication year - 2015
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0048
Subject(s) - codebook , linde–buzo–gray algorithm , computer science , vector quantization , quality (philosophy) , artificial intelligence , pattern recognition (psychology) , physics , quantum mechanics
The codebook design which determines the quality of the encoded images is an important problem in the vector quantisation technique. The Linde–Buzo–Gray (LBG) technique is a widely used algorithm in the codebook design. However, LBG algorithm is very sensitive to the initial codebook and tends to trap to the local minimum. In this study, a high‐quality initial codebook design method is proposed. The proposed method utilises both the mean characteristic value and variance characteristic value of training vectors to divide the training vectors into groups. Then codewords are selected from each group to generate an initial codebook. The experimental results demonstrate that the authors proposed method has a better performance in the initial codebook than that of the related methods.
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