End-to-end image dehazing by joint atmospheric scattering and WGAN model

Hongguo Zhang; Qingbing Sang

doi:10.1117/12.3008695

27 October 2023 End-to-end image dehazing by joint atmospheric scattering and WGAN model

Hongguo Zhang, Qingbing Sang

Proceedings Volume 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023); 129222W (2023) https://doi.org/10.1117/12.3008695
Event: The Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 2023, Xiamen, China

Abstract

The performance of most existing dehazing methods are limited by the independency of the transmission map estimation and atmospheric light. To ameliorate this, we present an algorithm based on both GANs models and atmospheric scattering. We first enhance the accuracy of transmission map estimation by constructing a multi-scale FC-DenseNet transmission map prediction network. To effectively avoids the issue of calculation errors caused by inaccurate prediction of the transmission map, a shallow residual dehazing network is also developed, which shares the learned weights of the transmission map prediction network. A multi-task loss function is constructed that dynamically optimizes the two networks simultaneously. To augment the generation of realistic images, a classical WGAN is used to fine-tune the generated transmission maps and dehazed images. The results demonstrate that our method has achieved significant improvements compared with the state-of-the-art (SOTA) methods.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hongguo Zhang and Qingbing Sang "End-to-end image dehazing by joint atmospheric scattering and WGAN model", Proc. SPIE 12922, Third International Conference on Electronics, Electrical and Information Engineering (ICEEIE 2023), 129222W (27 October 2023); https://doi.org/10.1117/12.3008695

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KEYWORDS

Image transmission

Atmospheric modeling

Gallium nitride

Data transmission

Atmospheric sciences

Data modeling

Education and training

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