Anomaly detection using simulated MTI data cubes derived from HYDICE data

The US Department of Energy is funding the development of the Multi-spectral Thermal Imager (MTI), a satellite-based multi-spectral (MS) thermal imaging sensor scheduled for launch in October 1999. MTI is a research and development (R and D) platform to test the applicability of multispectral and thermal imaging technology for detecting and monitoring signs of proliferation of weapons of mass destruction. During its three-year mission, MTI will periodically record images of participating government, industrial and natural sites in fifteen visible and infrared spectral bands to provide a variety of image data associated with weapons production activities. The MTI satellite will have spatial resolution in the visible bands that is five times better than LANDSAT TM in each dimension and will have five thermal bands. In this work, the authors quantify the separability between specific materials and the natural background by applying Receiver Operating Curve (ROC) analysis to the residual errors from a linear unmixing. The authors apply the ROC analysis to quantify performance of the MTI. They describe the MTI imager and simulate its data by filtering HYDICE hyperspectral imagery both spatially and spectrally and by introducing atmospheric effects corresponding to the MTI satellite altitude. They compare and contrast the individual effects on performance of spectral resolution, spatial resolution, atmospheric corrections, and varying atmospheric conditions