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

NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images