Unsupervised Spectral–Spatial Feature Extraction With Generalized Autoencoder for Hyperspectral Imagery

In this letter, we discuss unsupervised feature extraction on hyperspectral imagery (HSI) and propose a novel approach based on autoencoder (AE) networks to extract spectral-spatial features from HSI. Our approach takes the data relations into consideration, i.e., the input dependency with adjacent inputs, which the normal AE-based feature extractors often disregard. Specifically, the loss functio...