Algorithms for robust signal subspace identification in hyperspectral images: A comparative analysis

Abstract

In this work we present a comparative analysis of the performance of two recently proposed algorithms for signal subspace identification (SSI) and dimensionality reduction (DR) in hyperspectral data. Such SSI algorithms are robust to the presence of rare signal components and are particularly suitable when DR is adopted as a pre-processing step in small target detection applications.