Beneficiary of high order derivative spectrum in target detection

Ultraspectral data nature, allows the implementation of analytical chemistry techniques like derivative spectroscopy in hyperspectral images. Application of this method in remote sensing is due to the ability of derivative spectrum for resolving complex spectra of several target species within individual pixels, and the fact that derivatives of second or higher order are insensitive to illumination variations. So, it is expected that detecting signal sources in an individual pixel using the derivative spectrum be more effective. Moreover applying higher order derivatives in remote sensing applications have been neglected a lot. In this work 1^st to 5^th order derivative of a spectrum have been applied as the input for constrained energy minimization (CEM) algorithm and the altered CEM is introduced as Derivative CEM or “DCEM”. Results indicate the efficiency of using some orders of derivative spectrum in target detection and dependency of DCEM outputs on the target species.