Hyperspectral Remote Sensing Images Feature Extraction Based on Higher-Order Spectra

Abstract

Hyperspectral remote sensing images (HRSIs) contain rich spectral information, a HRSIs feature extraction method, i.e., higher-order spectra linear discriminant analysis (HOS-LDA) subspace method, is presented, which demonstrates that the calculation of higher-order spectra (HOS) is a kernel mapping with the inner product of HOS as the kernel function, and uses LDA to extract the HOS feature (HOSF) from the HOS of the spectral pixels of HRSIs according to a presented strategy of kernel space methods. To verify the efficiency of the deep feature of HOSF, a two-branch convolutional neural network (CNN), i.e., Two-CNN <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HOSF-spa</sub> , is designed with each branch fed with HOSF and spatial feature, respectively. A 3-dimensionality (3D) CNN, i.e., spa-hos-spe 3D-CNN, is designed, which is fed with the spatial-higher order spectra-spectral (spa-hos-spe) feature to evaluate the deep joint spa-hos-spe feature. The experimental results of three measured HRSIs show that: the presented HOS-LDA method has improved the classification rates compared with the LDA, spectral regression discriminant analysis (SRDA), kernel LDA (KLDA) methods by using support vector machine, Bayesian, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K</i> -nearest neighbor classifiers, which shows the efficiency of the presented HOSF; the presented Two-CNN <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HOSF-spa</sub> outperforms the two-branch CNN fed with spectral and spatial features and the two-branch CNNs fed with LDA, SRDA, KLDA extracted feature and spatial feature, which verifies the effectiveness of the deep HOSF; the presented spa-hos-spe 3D-CNN outperforms the 3D-CNN fed with spatial-spectral (spa-spe) feature, which shows that the deep spa-hos-spe feature is better than the deep spa-spe feature.