Improving Multispectral Mine Detection Methods By Compensating For Clutter

The detection of signals in clutter depends not only on good signal models and optimal processing, but also on accurate clutter models. An eective approch to land mine detection is the use of infrared imagery to detect thermal perturbations in the soil surface temperature caused by buried land mines. The purpose of this study is to investigate the value of augmenting long- and short-wave infrared imagery by red{green{blue visual imagery, in order to model vegetative clutter and thereby to detect land mines with greater probability and suer fewer false alarms. This study applies the shared mixture classier reported in earlier [14]. 1. HISTORICAL PERSPECTIVE The problem of safely and reliably detecting buried landmines has not yet been solved in any situation. We believe that any satisfactory device will require multiple sensors and high quality algorithms informed by physical and expert information and statistical data. For the last three years we have carried out a number of inves..