Network topology analysis: A new method for band selection

The hyperspectral bands are contiguous and highly correlated spectral bands. Band selection is often used to reduce the computational complexity for hyperspectral images. We proposed a new method for unsupervised band selection by using complex network to represent the spectral bands. The method completes the task with the objective of preserving the maximal information from original data in the selected bands. Both the divergences and connections between each hyperspectral band can be revealed from the topological characteristics of the generated network. We use the network topology as the criterion to identify the bands, and select the bands that can form the most approximate network comparing to the network of the original data. Experimental results demonstrate that, compared with traditional methods, the proposed algorithm can obtain accurate results with clear physical meaning and simple process.