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Learning to dehaze single hazy images, especially using a small training dataset is quite challenging.
Ranked #1 on Image Dehazing on O-Haze
Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.
Ranked #1 on Nonhomogeneous Image Dehazing on NH-HAZE validation
Conventional patch-based haze removal algorithms (e. g. the Dark Channel prior) usually performs dehazing with a fixed patch size.
In addition, to further enhance the performance of the method for haze removal, a patch-map-based DCP has been embedded into the network, and this module has been trained with the atmospheric light generator, patch map selection module, and refined module simultaneously.