A noise subspace projection approach to target signature detection and extraction in an unknown background for hyperspectral images

A noise subspace projection (NSP) approach to extraction and subpixel detection of target signatures in an unknown background is presented. The proposed NSP approach is derived from a recently developed subspace orthogonal projection (OSP) method and can be shown to be approximated by an adaptive filter with the optimal weight given by the Wiener-Hopf equation. As a result, the operator resulting from the NSP approach can be used as an OSP operator for scene classification and subpixel detection, on one hand, and also implemented as an adaptive filter, on the other. These advantages make the NSP approach very attractive in practical applications. In particular, the NSP operator takes advantage of the noise subspace projection to prevent from inverting correlation matrices, as required by an adaptive filter