关键词: 脑光学功能成像, 独立成分分析, 滤波

Abstract: In functional optical imaging，the very low SNR makes the sample covariance matrix have singularity，which brings the whitening the operation of the ICA denoising method to reduce the dimensionality，so the ICA denoising method will lost the signal detection ability.To resolve the problem，with the difference between the observed signals and the noise reconstructed by the initial ICA denoising method，a difference ICA（DICA） denoisng method is presented in this paper.Use the traditional filtering denoising method and the DICA denoisng method to deal with the simulated optical imaging datum in very low SNR，the results show that compared to the filtering denoising method，the DICA denoising method not only improves the denoising performance，but also can keep the output SNR while the input SNR changing.

Key words: function optical imaging, Independent Component Analysis（ICA）, filtering