关键词: 图像盲分离, 自适应学习率, 独立分量分析

Abstract: It is the technique of Independent Component Analysis（ICA）that be mainly researched in the paper. The Fast Independent Component Analysis has the advantage of sample structure, fast convergence, easy to use and so on, but it requests the data independent of each other rigorously. In fact, there are many relationships in the real observation data sets. So, when these things happen, traditional Fast ICA convergences very slowly even fail. We solve the problem by proposed an adaptive learning rate to improve the convergence performance. The experiment is applied to image separation and compared to the traditional methods in the convergence speed. It is easy to see this method is very efficient after calculating the Peak Signal Noise Ratio (PSNR) of the obtained images.

Key words: image blind separation, adapt learning rate, independent component analysis