ABSTRACT
ORASIS (the Optical Real-Time Adaptive Spectral Identification System) is a series of algorithms developed at the Naval Research Lab for the analysis of HyperSpectral Image (HSI) data. ORASIS is based on the Linear Mixing Model (LMM), which assumes that the individual spectra in a given HSI scene may be decomposed into a set of in-scene constituents known as endmembers. The algorithms in ORASIS are designed to identify the endmembers for a given scene, and to decompose (or demix) the scene spectra into their individual components. Additional algorithms may be used for compression and various post-processing tasks, such as terrain classification and anomaly detection. In this chapter, we present a parallel version of the ORASIS algorithm that was recently developed as part of a Department of Defense program on hyperspectral data exploitation.
