DocumentCode :
2910824
Title :
A novel Genetic Particle-Pair Optimizer for Vector Quantization in image coding
Author :
Liao, Huilian ; Ji, Zhen ; Wu, Q.H.
Author_Institution :
Texas Instrum. DSPs Lab., Shenzhen Univ., Shenzhen
fYear :
2008
fDate :
1-6 June 2008
Firstpage :
708
Lastpage :
713
Abstract :
This paper presents a novel genetic particle-pair optimizer (GPPO) for vector quantization of image coding. GPPO only applies a particle-pair that consists of two particles, which contributes to the relief of huge computation load in most existing vector quantization algorithms. GPPO combines the advantage both in genetic algorithms and particle swarm optimization, due to the use of genetic operators and particle operators at each generation. Experimental results have demonstrated that the quality of the codebook design optimized by GPPO is better than that optimized respectively by fuzzy K-means (FKM), fuzzy reinforcement learning vector quantization (FRLVQ, improved FRLVQ which uses fuzzy vector quantization (FVQ as post-process, called FRLVQ-FVQ, and particle-pair optimizer (PPO). GPPO provides a satisfactory solution to vector quantization, and shows a steady trend of improvement in the quality of codebook design. The dependence of the final codebook on the selection of the initial codebook is also reduced.
Keywords :
genetic algorithms; image coding; particle swarm optimisation; vector quantisation; codebook design; genetic algorithm; genetic particle-pair optimizer; image coding; particle swarm optimization; vector quantization; Algorithm design and analysis; Convergence; Design optimization; Genetic algorithms; Genetic engineering; Image coding; Learning; Particle swarm optimization; Process design; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1822-0
Electronic_ISBN :
978-1-4244-1823-7
Type :
conf
DOI :
10.1109/CEC.2008.4630873
Filename :
4630873
Link To Document :
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