A Comparison of Hierarchical Classification Processes Based on Hyperspectral Image

In this study, the performances of hyperspectral image classification using three max-cut based BHC schemes are compared. The first one is original BHC scheme and the second is applied feature extraction in the root node. The last is applied feature extraction in the each non-leaf node. The real data experimental results show that applying feature extraction in the each non-leaf node is the best strategy. Among the combinations of two feature extraction methods, DAFE and NWFE and three base classifiers, using NWFE and ML base classifier can reach the best performance.