Target discrimination of man-made objects using passive polarimetric signatures acquired in the visible and infrared spectral bands

Abstract

Surveillance operations and search and rescue missions regularly exploit electro-optic imaging systems to detect targets of interest in both the civilian and military communities. By incorporating the polarization of light as supplementary information to such electro-optic imaging systems, it is possible to increase their target discrimination capabilities, considering that man-made objects are known to depolarized light in different manner than natural backgrounds. As it is known that electro-magnetic radiation emitted and reflected from a smooth surface observed near a grazing angle becomes partially polarized in the visible and infrared wavelength bands, additional information about the shape, roughness, shading, and surface temperatures of difficult targets can be extracted by processing effectively such reflected/emitted polarized signatures. This paper presents a set of polarimetric image processing algorithms devised to extract meaningful information from a broad range of man-made objects. Passive polarimetric signatures are acquired in the visible, shortwave infrared, midwave infrared, and longwave infrared bands using a fully automated imaging system developed at DRDC Valcartier. A fusion algorithm is used to enable the discrimination of some objects lying in shadowed areas. Performance metrics, derived from the computed Stokes parameters, characterize the degree of polarization of man-made objects. Field experiments conducted during winter and summer time demonstrate: 1) the utility of the imaging system to collect polarized signatures of different objects in the visible and infrared spectral bands, and 2) the enhanced performance of target discrimination and fusion algorithms to exploit the polarized signatures of man-made objects against cluttered backgrounds.