Image vector quantization algorithm via honey bee mating optimization

Ming Huwi Horng, Ting Wei Jiang

研究成果: Article同行評審

44 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)1382-1392
頁數11
期刊Expert Systems With Applications
38
發行號3
DOIs
出版狀態Published - 2011 3月

All Science Journal Classification (ASJC) codes

  • 一般工程
  • 電腦科學應用
  • 人工智慧

指紋

深入研究「Image vector quantization algorithm via honey bee mating optimization」主題。共同形成了獨特的指紋。

引用此