Single image dehazing - Open Access .click

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Single image dehazing is a challenging ill-posed problem. Existing datasets for training deep learning-based methods can be generated by hand-crafted or synthetic schemes. However, the former often suffers from small scales, while the latter forces models to learn scene depth instead of haze distribution, decreasing their dehazing ability.
Xu, Honglei, Shu, Yan, Liu, Shaohui
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SINGLE IMAGE DEHAZING USING PHYSICS-INFORMED CONVOLUTIONAL AUTOENCODER

Модели, системы, сети в экономике, технике, природе и обществе
Background. Generally, haze can be considered to be one of the most fundamental phenomena causing image visibility degradation. Numerous haze removal approaches have been proposed and most of them have achieved significant progress.
A.V. Kozhevnikova, M.A. Mitrokhin
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MCRFS-Net: single image dehazing based on multi-scale contrastive regularization and frequency selection. [PDF]

Sci Rep
Qin Q, Shui L, Zhang Y, Song S, Jiang J.
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Alpha-DehazeNet: single image dehazing <i>via</i> RGBA haze modeling and adaptive learning. [PDF]

PeerJ Comput Sci
He J, Li R.
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Single-image dehazing method based on Rayleigh Scattering and adaptive color compensation. [PDF]