An insight into the architecture of the Encoder-Decoder Network with Guided Transmission Map (EDN-GTM), a novel and effective single image dehazing scheme, is presented in this paper. The EDN-GTM takes a conventional RGB hazy image in conjunction with the corresponding transmission map estimated by the dark channel prior (DCP) approach as inputs of the network. The EDN-GTM adopts an enhanced structure of U-Net developed for dehazing tasks and the resulting EDN-GDM has shown state-of-the-art performances on benchmark dehazing datasets in terms of PSNR and SSIM metrics. In order to give an in-depth understanding of the well-designed architecture which largely contributes to the success of the EDN-GTM, extensive experiments and analysis from selecting the core structure of the scheme to investigating advanced network designs are presented in this paper.

翻译：本文深入剖析了引导传输图编码器-解码器网络（EDN-GTM）的架构，这是一种新颖且有效的单幅图像去雾方案。EDN-GTM将常规RGB雾霾图像与通过暗通道先验（DCP）方法估计的对应传输图作为网络输入。该网络采用为去雾任务改进的U-Net增强结构，由此产生的EDN-GTM在基准去雾数据集上，以PSNR和SSIM指标衡量，展现出当前最优的性能。为了深入理解这一精心设计的架构（该架构对EDN-GTM的成功贡献显著），本文从方案核心结构的选择到先进网络设计的探索，进行了广泛的实验与分析。