Single-scale Residual Dense Dehazing Network
Nian Wang, Aihua Li, Zhigao Cui, Yanzhao Su, Yunwei Lan · Journal of Physics Conference Series · 2021
Abstract Recently, image dehazing algorithm has been widely used in the preprocessing of target tracking and pattern recognition. A large number of end-to-end convolutional networks have achieved good results in dehazing by image translation. In this paper, we use Residual Dense structure, which has been prove effective in high resolution reconstruction, to build feature extract block, and stack these block to form a single-scale dehazing network. In order to further enhance the performance, we convey the feature of shallow layer to deep layer by channel concatenation. The results show that our network has achieved good results in both the synthetic haze removal and the real haze removal.