Detection of buried mines and explosive objects using dual-band thermal imagery

We demonstrate the development and use of novel image processing methods to combine dual-band (MWIR and LWIR) images from SELEX GALILEO's Condor II camera to extract characteristics of observed scenes comprising buried mines and explosive objects. We discuss the development of a statistical processing technique to extract the different characteristics of the two bands. We further present a statistical classifier used to detect targets on independently trained images with a high detection probability and low false negative rates and discuss methods to mitigate the impact of false positives through the selective processing of image regions and the contextual interpretation of the scene content.