Single Image Dehazing using Positive Correlation under Gradient Constraint
Yi Lai, Chaoyan Wu, Bingheng Li, Ying Liu · 2019
We propose an accurate and efficient dehazing method. First of all, we obtain the positive relationship between the minimum channel of a hazy image and the corresponding depth map. Based on this relationship and the gradient constraint, the depth map is estimated. And then, in a hazy image, according to the derivation that the atmosphere light relates to the brightest pixels, quad-tree subdivision algorithm is introduced to achieve the region with maximum intensity which can be further utilized to calculate the atmosphere light. Finally, the haze-free image is restored using the traditional atmospheric scattering model. Experimental results demonstrates that the proposed method can not only restore the high-grade image but also have a lower time consumption compared to the state-of-the-art methods.