# DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing Source: [DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing]() Collection index: [llms.txt]() Data updated: 2025-10-26T06:50:43.062Z Authors: Minghan Fu, Huan Liu, Yankun Yu, Jun Chen, Keyan Wang Published: 2021-04-18T16:58:11.000Z ## Abstract Hazy images are often subject to color distortion, blurring, and other visible quality degradation. Some existing CNN-based methods have great performance on removing homogeneous haze, but they are not robust in non-homogeneous case. The reasons are mainly in two folds. Firstly, due to the complicated haze distribution, texture details are easy to be lost during the dehazing process. Secondly, since the training pairs are hard to be collected, training on limited data can easily lead to over-fitting problem. To tackle these two issues, we introduce a novel dehazing network using 2D discrete wavelet transform, namely DW-GAN. Specifically, we propose a two-branch network to deal with the aforementioned problems. By utilizing wavelet transform in DWT branch, our proposed method can retain more high-frequency knowledge in feature maps. In order to prevent over-fitting, ImageNet pre-trained Res2Net is adopted in the knowledge adaptation branch. Owing to the robust feature representations of ImageNet pre-training, the generalization ability of our network is improved dramatically. Finally, a patch-based discriminator is used to reduce artifacts of the restored images. Extensive experimental results demonstrate that the proposed method outperforms the state-of-the-arts quantitatively and qualitatively. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Dehazing on Ambient6K (test)](): Dehazing; Ambient6K (test); PSNR: 20.969. - [Non-homogeneous Image Dehazing on NH-HAZE (test)](): Non-homogeneous Image Dehazing; NH-HAZE (test); PSNR: 22.13. ## Original sources and implementation [Original paper]() [PDF]()