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Image vector quantization algorithm via honey bee mating optimization
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DOI：10.1016/j.eswa.2010.07.037.png)
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摘要
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The vector quantization (VQ) was a powerful technique in the applications of digital image compression. The traditionally widely used method such as the Linde-Buzo-Gray (LBG) algorithm always generated local optimal codebook. Recently, particle swarm optimization (PSO) is adapted to obtain the near-global optimal codebook of vector quantization. An alternative method, called the quantum particle swarm optimization (QPSO) had been developed to improve the results of original PSO algorithm. In this paper, we applied a new swarm algorithm, honey bee mating optimization, to construct the codebook of vector quantization. The results were compared with the other three methods that are LBG, PSO-LBG and QPSO-LBG algorithms. Experimental results showed that the proposed HBMO-LBG algorithm is more reliable and the reconstructed images get higher quality than those generated from the other three methods. (C) 2010 Elsevier Ltd. All rights reserved.
Keyword:
Vector quantization
LBG algorithm
Particle swarm optimization
Quantum particle swarm optimization
Honey bee mating optimization
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7.5
论文数:
3.0W
被引数:
10.2W
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