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https://doi.org/10.1109/icmew.2018.8551504
Copy DOIPublication Date: Jul 1, 2018 |
Citations: 24 |
Single image haze removal is an important task in computer vision. However, haze removal is an extremely challenging problem due to it is massively ill-posed, which is that we need to estimate the transmission and the corresponding haze-free pixel from a single color measurement at each pixel. In this paper, we propose a new deep learning based method for removing haze from single input image. First, we estimate a transmission map via joint estimation of clear image details and transmission map, which is different from traditional methods which only estimating a transmission map for a hazy image. Second, we use a global regularization method to eliminate the halos and artifacts. Experimental results demonstrate that our method outperforms the other state-of-the-art dehazing methods.
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