Multiple band selection for anomaly detection in hyperspectral imagery

Abstract

This paper develops a new approach to band selection (BS), called multiple band selection (MBS), which does not require band prioritization to select bands but rather relies on applications to select bands. Its idea is to first use virtual dimensionality (VD) to determine the number of multiple bands needed to be selected. Then MBS is performed by two major iterative process, sequential multiple band selection (SQ-MBS) and successive multiple band selection (SC-MBS). In order to evaluate the performance of MBS anomaly detection is used its application for demonstration.