Figure 1.

Illustrations of popular features used in HSI classification. Early CNN-based HSI classification methods are either based on raw spectral pixel feature [22] in (a) or spectral pixel patch feature [37] in (b). As shown in (c), [32] adopts a random sampling scheme across the entire training set to construct a large number of labeled pixel pair features (PPF) pairs. The proposed spatial pixel pair feature (SPPF) feature chooses a tight eight-neighbor as $N\left(x_0\right)$, from which SPPF pairs are built, such as $\left\{x_0,x_1\right\}$, $\left\{x_0,x_2\right\}$, etc. (a) Raw spectral pixel feature; (b) spectral pixel patch feature; (c) PPF feature; (d) proposed SPPF feature.