A Research on the Combination Strategies of Multiple Features for Hyperspectral Remote Sensing Image Classification

Figure 12

Classification maps of the PU dataset with features under a manifold-based framework; (a)–(e), respectively, represent different groups of input features: spectral features, GF, TF, GF combined with TF, and all features along with the spectral features. is the feature dimension for input.

(a) SPEC

(b) GF

(c) TF

(d) GF + TF

(e) GF + TF + SPEC