Blind Separation of Image Based on Wavelet Transform and Kernel Independent Component Algorithm
Chen Con · Journal of Sichuan University of Science & Engineering · 2014
Blind sources separation technology plays a significant role in recover and reconstruction of the pollution image. In recent years,several algorithms of the blind source separation have been studied in which the kernel independent component algorithm(KICA) is the optimal one in case of noiseless. On the other hand,the conventional methods have poor performance for the de-noising separation of the mixed noised image. In order to resolve this problem,a algorithm combined the wavelet de-noising approach and the KICA technique is proposed to de-noising separate the mixed noised image. Finally,some simulation results are given to illustrate that the method can reduce the influence of the noise effectively,and achieve the better de-noising separation of the image.