"Region-Aware Hierarchical Latent Feature Representation Learning-Guide" by Jun Wang, Chang Tang et al.
Hyperspectral band selection aims to identify an optimal subset of bands for hyperspectral images (HSIs). For most existing clustering-based band selection methods, they directly stretch each band into a single feature vector and employ the pixelwise features to address band redundancy. In this way, they do not take full consideration of the spatial information and deal with the importance of different regions in HSIs, which leads to a nonoptimal selection. To address these issues, a region-awar...
Clustering Algorithms Clustering Methods Feature Extraction Feature Fusion Ierarchical Latent Feature Learning Yperspectral Band Selection
Source: uow.edu.au