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DehazeNet: An End-to-End System for Single Image Haze Removal
The key to achieve haze removal is to estimate a medium transmission map for an input hazy image.
Single Image Haze Removal using a Generative Adversarial Network
Traditional methods to remove haze from images rely on estimating a transmission map.
PMS-Net: Robust Haze Removal Based on Patch Map for Single Images
Conventional patch-based haze removal algorithms (e. g. the Dark Channel prior) usually performs dehazing with a fixed patch size.
COMPUTATIONAL PHENOTYPING DENOISING IMAGE DEHAZING IMAGE RESTORATION NONHOMOGENEOUS IMAGE DEHAZING SINGLE IMAGE DEHAZING SINGLE IMAGE DERAINING SINGLE IMAGE HAZE REMOVAL
Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks
We train a generative adversarial network to learn the probability distribution of clear images conditioned on the haze-affected images using the Wasserstein loss function, using a gradient penalty to enforce the Lipschitz constraint.
PMHLD: Patch Map Based Hybrid Learning DehazeNet for Single Image Haze Removal
IEEE Transaction on Image Processing 2020
• weitingchen83/Dehazing-PMHLD-Patch-Map-Based-Hybrid-Learning-DehazeNet-for-Single-Image-Haze-Removal-TIP-2020
• 
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.
COMPUTATIONAL PHENOTYPING DENOISING IMAGE DEHAZING IMAGE RESTORATION NONHOMOGENEOUS IMAGE DEHAZING SINGLE IMAGE DERAINING SINGLE IMAGE HAZE REMOVAL
Single Image Haze Removal Using Dark Channel Prior
The dark channel prior is a kind of statistics of outdoor haze-free images.