Image vector quantization algorithm via honey bee mating optimization

作     者：Horng, Ming-Huwi Jiang, Ting-Wei 

作者机构：Natl Pingtung Inst Commerce Dept Comp Sci & Informat Engn Pingtung Taiwan 

出 版 物：《EXPERT SYSTEMS WITH APPLICATIONS》 (专家系统及其应用)

年 卷 期：2011年第38卷第3期

页      面：1382-1392页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Science Council  ROC [NSC 98-2221-E-251-001] 

主　　题：Vector quantization LBG algorithm Particle swarm optimization Quantum particle swarm optimization Honey bee mating optimization 

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. (C) 2010 Elsevier Ltd. All rights reserved.