Global Filter of Fusing Near-Infrared and Visible Images in Frequency Domain for Defogging

Linli Xu, Peixian Liang, Jing Han, Lianfa Bai, Danny Z. Chen

Abstract: Exploiting complementary advantages of different reflection and scattering properties of near-infrared (NIR) images and visible (VIS) images, this letter first proposes a defogging model for single image input and then develops an extended model, a fusion model for NIR and VIS color images, to enhance the visibility of image objects in scattering environments. Our fusion model enhances the extracted details of NIR and VIS images by filtering with our defogging model in the frequency domain that takes into account the energy preservation of these two types of images in addition to the high resolution of the fused results. Finally, based on the initial fusion, we propose a color retention mapping method to keep the fusion results free of color distortion. Experimental results demonstrate that our proposed method not only achieves good defogging effect, but also can effectively combine the complementary NIR and VIS information in image color and visibility.