Sensor band selection for multispectral imaging via average normalized information

The information-rich scene descriptors created by multispectral sensors can act as a bottleneck in further analysis. Many of the spectral band selection methods treat the two underlying tasks (feature bands selection and redundancy reduction) in isolation. Furthermore, the majority of the work assumes reflectance data. However, the captured surface radiance varies with scene geometry and illumination. We propose a new band selection method, which uses spectral gradient entropy to choose bands that are more stable to such variations. Equally important, our measurement, the average normalized information (ANI) of a set of selected bands, combines feature band selection and band redundancy together. In our experiments, ANI exhibited comparable performance with mutual information on reflectance data but outperformed mutual information when applied on surface radiance data.

• Type: Journal
• Year: 2006
• Where: JRTIP
• Authors: Hongzhi Wang, Elli Angelopoulou
• Keywords: Band Selection, Information-rich Scene Descriptors, JRTIP 2006, Surface Radiance