A new fusion algorithm for shadow penetration using visible and midwave infrared polarimetric images

This paper presents a new polarimetric image fusion algorithm to discriminate objects lying in shadow areas against cluttered backgrounds. Polarimetric signatures of man-made objects are collected using a fully automated passive polarimetric sensor-suite operating in the visible, shortwave, midwave, and longwave infrared bands. The polarization state of the radiation emitted and/or reflected from objects' surfaces and surrounding background is characterized using the total intensity, the degree of linear polarization, and the phase of the polarization. Using two distinct scenarios, experimental results demonstrate the utility of the proposed image fusion algorithm to exploit the polarized signatures of man-made objects in the visible and midwave infrared bands for shadow penetration purposes.