Compressive Hyperspectral Imaging and Anomaly Detection

Compressive Sensing (CS) is an emerging field based on the realization that a small collection of nonadaptive linear projections of a compressible signal contain enough information for reconstruction and processing. Expanding on this emerging technology, this project will make significant contributions in the following ways to the problem of anamoly detection in hyperspectral imagery: (i) increase our capacity for hyperspectral image acquisition developing new imaging and spectroscopic systems; (ii) expand the frontiers of CS from signal recovery to new applications including knowledge learning including anamoly detection; and (iii) strengthen our ability for extracting knowledge from huge data sets such as hyperspectral images beyong current limits imposed by existing computational resources and methods. BENEFIT: Our results have the potential to be economically revolutionary given the growing importance of digital imaging in many endeavors.)