A Hyperspectral Remote Sensing Image Classification Method Based On Multi-Spatial Information

In the field of hyperspectral remote sensing image classification, spatial and spectral feature fusion can improve the effect of classification. A multi-feature spectral and spatial classification method for hyperspectral images was proposed. In the post-processing procedure, the salt-and-pepper noises were removed by using superpixel information. It was also used in the pre-processing procedure, and the feature vector of pixels was weighted by superpixel information. The experiment results show that the results of proposed method are better than the present methods.