[Hyperspectral Band Selection Based on Spectral Clustering and Inter-Class Separability Factor].

With the development of remote sensing technology and imaging spectrometer, the resolution of hyperspectral remote sensing image has been continually improved, its vast amount of data not only improves the ability of the remote sensing detection but also brings great difficulties for analyzing and processing at the same time. Band selection of hyperspectral imagery can effectively reduce data redundancy and improve classification accuracy and efficiency. So how to select the optimum band combination from hundreds of bands of hyperspectral images is a key issue.