Research of Image Blind Separation Method Based on QPSO and ICA
Dai Lin-na · Journal of Zhengzhou University · 2012
In this paper,we introduce the Independent Component Analysis(ICA) and Quantum Particle Swarm Optimization(PSO) briefly.As the ordinary gradient algorithm of ICA technology is easy to fall into local optimum,we proposed quantum-behavior based particle swarm optimization and independent component analysis for blind source separation combining new algorithms.This algorithm takes negative entropy as the objective function of independent component analysis,replaces the ordinary gradient algorithm with QPSO algorithm and separates the instantaneous mixed signals,All the steps of this algorithm are given in this paper.Experiment is show that the proposed algorithm can effectively achieve the image of the blind source separation.Compared with other algorithms,this algorithm shows better performance.