Multispectral illumination and image processing techniques for active millimeter-wave concealed object detection
 
Multispectral illumination and image processing techniques for active millimeter-wave concealed object detection 
 
Lixiao Zhang, Johan Stiens, Amna Elhawil, Roger Vounckx, James Wyant
 
Abstract 

Active millimeter-wave imaging systems for concealed object detection offer the possibility of much higher image contrast than passive systems, especially in indoor applications. By studying active millimeter-wave images of different test objects derived in the W band, we show that multispectral illumination is critical to the detectability of targets. We also propose to use image change detection techniques, including image differencing, normalized difference vegetation index, and principle component analysis to process the multispectral millimeter-wave images. The results demonstrate that multispectral illumination can significantly reveal the object features hidden by image artifacts and improve the appearance of the objects.