  Image dehazing is an ill-posed problem that has been extensively studied in
the recent years. The objective performance evaluation of the dehazing methods
is one of the major obstacles due to the lacking of a reference dataset. While
the synthetic datasets have shown important limitations, the few realistic
datasets introduced recently assume homogeneous haze over the entire scene.
Since in many real cases haze is not uniformly distributed we introduce
NH-HAZE, a non-homogeneous realistic dataset with pairs of real hazy and
corresponding haze-free images. This is the first non-homogeneous image
dehazing dataset and contains 55 outdoor scenes. The non-homogeneous haze has
been introduced in the scene using a professional haze generator that imitates
the real conditions of hazy scenes. Additionally, this work presents an
objective assessment of several state-of-the-art single image dehazing methods
that were evaluated using NH-HAZE dataset.
