Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Particle Swarm Optimization Learning Fuzzy Systems Design
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy vector quantization algorithms and their application in image compression
IEEE Transactions on Image Processing
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Codebook design of VQ (Vector Quantization) is a global optimization problem. The LBG algorithm depends upon the initial codebook and is prone to converge to a local optimal solution. To solve the problem, adopt PSO (Particle Swarm Optimization) to design the optimal codebook of image vector quantization and present PSO-VQ (PSO Vector Quantization) algorithm. According to PSO-VQ, a particle indicates a codebook and the optimal codebook is obtained from iterations of the initial codebooks by method of the particle evolvement. To ensure the solution converge to the global optimal codebook, the authors presented the PCO (Particle Coherent Operation), by which the code vectors of each initial codebook are sorted in ascending order based on the average gray value of the pixels in the code vector, and so that the inner structures of all the particles are essentially identical. The experimental results show that the PSO-VQ algorithm is feasible and effective, as well as develops the application of the PSO.