Fusion-Based Edge and Color Recovery Using Weighted Near-Infrared Image and Color Transmission Maps for Robust Haze Removal

Abstract

Various haze removal methods based on the atmospheric scattering model have been presented in recent years. Most methods have targeted strong haze images where light is scattered equally in all color channels. This paper presents a haze removal method using near-infrared (NIR) images for relatively weak haze images. In order to recover the lost edges, the presented method first extracts edges from an appropriately weighted NIR image and fuses it with the color image. By introducing a wavelength-dependent scattering model, our method then estimates the transmission map for each color channel and recovers the color more naturally from the edge-recovered image. Finally, the edge-recovered and the color-recovered images are blended. In this blending process, the regions with high lightness, such as sky and clouds, where unnatural color shifts are likely to occur, are effectively estimated, and the optimal weighting map is obtained. Our qualitative and quantitative evaluations using 59 pairs of color and NIR images demonstrated that our method can recover edges and colors more naturally in weak haze images than conventional methods.