An information theoretical approach to multiple-band selection for hyperspectral imagery

摘要

An information theoretical approach to multiple-band selection (MBS) is presented in this paper. It formulates a MBS problem as a channel capacity problem by considering the original band set as a channel input space and the selected multiple band set as a channel output space with the channel transition probabilities specified by band discrimination between original bands and selected bands. Then bands are selected by iteratively finding a best possible input space that yields the maximal channel capacity. As a result, there is no need of band prioritization and de-correlation generally required by traditional band selection (BS). Two iterative algorithms are developed for MBS, sequential channel capacity MBS (SQ-CCMBS) and successive channel band selection (SC-CCMBS).