Abstract：ICA coefficients are non-Gaussian in independent component analysis model. The high-order statistical features are used in characterization of non-Gaussian feature. The combined moments of variance, skewness and kurtosis are proposed to describe the ICA coefficients probability distributing characteristic. The combined moments are used in texture classification and it can achieve better classification performance than the previously reported ICA features. Furthermore, L-moments are used to improve robustness in moments estimation and to get better performance than the ordinary moments.
徐小红，杨学志，杨德美，高隽. ICA系数的高阶统计特征在纹理分类中的应用*[J]. 模式识别与人工智能, 2009, 22(3): 499-505.
XU Xiao-Hong, YANG Xue-Zhi, YANG De-Mei, Gao Jun. Application of Higher-Order Statistics Features of ICA Coefficients in Texture Classification. , 2009, 22(3): 499-505.
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