Cascade superpixel regularized Gabor feature fusion for hyperspectral image classification

A 3-D Gabor wavelet provides an effective way to obtain the spectral-spatial-fused features for hyperspectral image, which has shown advantageous performance for material classification and recognition. In this paper, instead of separately employing the Gabor magnitude and phase features, which, respectively, reflect the intensity and variation of surface materials in local area, a cascade superpixel regularized Gabor feature fusion (CSRGFF) approach has been proposed. First, the Gabor filters with particular orientation.