Constrained multiple band selection for hyperspectral imagery

Abstract

A recent developed band selection, called constrained band selection (CBS), makes use of constrained energy minimization (CEM) to constrain a single band to calculate its priority for band selection (BS). This paper extends such CEM-BS to a constrained multiple band selection (CMBS)-based method, to be called linearly constrained minimum variance multiple band-constrained selection (CMBS), which uses LCMV to constrain multiple bands to perform band subset selection. Since CMBS selects multiple bands as a band subset as a whole it does not require band prioritization (BP) or band de-correlation (BD) as traditional band selection (BS) usually does. However, CMBS is traded for one challenging issue, which is excessive computational complexity because it requires running through a total number of subsets in the power set of a full band set compared to BS which only needs to select one band at a time. In order to avoid exhaustive search for all band subsets in it power set, a sequential CMBS, successive CMBS (SC-CMBS) is developed to ease computational complexity.