Human visual system-based image fusion for surveillance applications

Image fusion algorithms combine images obtained using different sensors into a single image to provide contextual enhancement of the scene being observed. The fusion of images obtained using infrared (IR) and visible light (VL) cameras are particularly appealing for security applications such as surveillance and concealed weapon detection. In this paper, a new image fusion algorithm is proposed, which considers both the luminance masking feature of the human visual system (HVS) and the nature of the pertinent information in IR images in the context of surveillance applications. Experimental results illustrate the improved performance of the proposed algorithm by both qualitative and quantitative means.