Remove haze in a single image by using three components
Remove haze in a single image by using three components
From Synthetic to Real: Image Dehazing Collaborating with Unlabeled Real Data
arXiv paper abstract https://arxiv.org/abs/2108.02934v1
arXiv PDF paper https://arxiv.org/pdf/2108.02934v1.pdf
Single image dehazing is a challenging task, for which the domain shift between synthetic training data and real-world testing images usually leads to degradation of existing methods.
... propose a novel image dehazing framework collaborating with unlabeled real data.
... develop a disentangled image dehazing network (DID-Net), which disentangles the feature representations into three component maps, i.e.
the latent haze-free image,
the transmission map, and
the global atmospheric light estimate, respecting the physical model of a haze process.
... make comparison with 13 state-of-the-art dehazing methods
... method has obvious quantitative and qualitative improvements over the existing methods.
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