Cointegration theory for adaptive target detection in hyperspectral images

This paper investigates the usage of Johansen Cointegration Test for adaptive target detection with hyperspectral remote sensing data. Johansen Cointegration Test aims at mining long-term equilibrium relationship, which refers to the condition that if pairs of non-stationary series share similar tendencies, their linear combination could be stationary. Hyperspectral data are highly non-stationary series, but there should be similar patterns among the hyperspectral response curves of same materials. To be treated as derivative series, given hyperspectral response curves will be matched with the standard spectrum via Johansen Cointegration Test. The test statistics will be compared to a preset threshold to judge whether they are target or not. Quantitative experiments show that the proposed method performs better than a few other adaptive detection methods tested.