  Reliable and exact assessment of visibility is essential for safe air
traffic. In order to overcome the drawbacks of the currently subjective reports
from human observers, we present an approach to automatically derive visibility
measures by means of image processing. It first exploits image based estimation
of the atmospheric transmission describing the portion of the light that is not
scattered by atmospheric phenomena (e.g., haze, fog, smoke) and reaches the
camera. Once the atmospheric transmission is estimated, a 3D representation of
the vicinity (digital surface model: DMS) is used to compute depth measurements
for the haze-free pixels and then derive a global visibility estimation for the
airport. Results on foggy images demonstrate the validity of the proposed
method.
