  We propose a fusion algorithm for haze removal that combines color
information from an RGB image and edge information extracted from its
corresponding NIR image using Haar wavelets. The proposed algorithm is based on
the key observation that NIR edge features are more prominent in the hazy
regions of the image than the RGB edge features in those same regions. To
combine the color and edge information, we introduce a haze-weight map which
proportionately distributes the color and edge information during the fusion
process. Because NIR images are, intrinsically, nearly haze-free, our work
makes no assumptions like existing works that rely on a scattering model and
essentially designing a depth-independent method. This helps in minimizing
artifacts and gives a more realistic sense to the restored haze-free image.
Extensive experiments show that the proposed algorithm is both qualitatively
and quantitatively better on several key metrics when compared to existing
state-of-the-art methods.
