The matched subspace detector with interaction effects. (August 2017) - Wang, Ziyu; Xue, Jing-Hao
Highlights: Propose a new hyperspectral target-detection method called MSDinter. Introduce "interaction effects" into the popular matched subspace detector (MSD). Model the target-background interaction in hypothesis testing. Demonstrate superior performance of MSDinter on hyperspectral imaging datasets. Abstract: This paper aims to propose a new hyperspectral target-detection method termed the matched subspace detector with interaction effects (MSDinter). The MSDinter introduces "interaction effects" terms into the popular matched subspace detector (MSD), from regression analysis in multivariate statistics and the bilinear mixing model in hyperspectral unmixing. In this way, the interaction between the target and the surrounding background, which should have but not yet been considered by the MSD, is modelled and estimated, such that superior performance of target detection can be achieved. Besides deriving the MSDinter methodologically, we also demonstrate its superiority empirically using two hyperspectral imaging datasets.