Visible and NIR image fusion using weight-map-guided Laplacian–Gaussian pyramid for improving scene visibility

Image visibility is affected by the presence of haze, fog, smoke, aerosol, etc. Image dehazing using either single visible image or visible and near-infrared (NIR) image pair is often considered as a solution to improve the visual quality of such scenes. In this paper, we address this problem from a visible–NIR image fusion perspective, instead of the conventional haze imaging model. The proposed algorithm uses a Laplacian–Gaussian pyramid based multi-resolution fusion process, guided by weight maps generated using local entropy, local contrast and visibility as metrics that control the fusion result. The proposed algorithm is free from any human intervention, and produces results that outperform the existing image-dehazing algorithms both visually as well as quantitatively. The algorithm proves to be efficient not only for the outdoor scenes with or without haze, but also for the indoor scenes in improving scene visibility.