  High-quality dehazing performance is highly dependent upon the accurate
estimation of transmission map. In this work, the coarse estimation version is
first obtained by weightedly fusing two different transmission maps, which are
generated from foreground and sky regions, respectively. A hybrid variational
model with promoted regularization terms is then proposed to assisting in
refining transmission map. The resulting complicated optimization problem is
effectively solved via an alternating direction algorithm. The final haze-free
image can be effectively obtained according to the refined transmission map and
atmospheric scattering model. Our dehazing framework has the capacity of
preserving important image details while suppressing undesirable artifacts,
even for hazy images with large sky regions. Experiments on both synthetic and
realistic images have illustrated that the proposed method is competitive with
or even outperforms the state-of-the-art dehazing techniques under different
imaging conditions.
