Research Article
Image Defogging Algorithm Based on Inception Mechanism
@INPROCEEDINGS{10.1007/978-3-031-04245-4_27, author={Jiahao Geng and Zhuang Miao and Kezheng Lin}, title={Image Defogging Algorithm Based on Inception Mechanism}, proceedings={6GN for Future Wireless Networks. 4th EAI International Conference, 6GN 2021, Huizhou, China, October 30--31, 2021, Proceedings}, proceedings_a={6GN}, year={2022}, month={5}, keywords={Pattern recognition Image defogging Deep learning Attention mechanism PatchGAN}, doi={10.1007/978-3-031-04245-4_27} }- Jiahao Geng
Zhuang Miao
Kezheng Lin
Year: 2022
Image Defogging Algorithm Based on Inception Mechanism
6GN
Springer
DOI: 10.1007/978-3-031-04245-4_27
Abstract
In order to solve the problem that the existing defogging algorithms can’t differentiate according to the characteristics of different regions of the fogged image, an Image Defogging Algorithm Based on Inception Mechanism is proposed(I-defog algorithm). The attention mechanism is added to the algorithm to adaptively assign weights to the features of different regions; It is more accurate and effective to use the module with perception mechanism to predict the global value. The predicted value, transmittance and foggy image are input into the atmospheric scattering model to get the defogging image, and the defogging image is input into the Markov discriminant (PatchGAN) to judge whether it is true or not. The results show that the algorithm achieves good defogging effect on both indoor and outdoor images, and improves the brightness and saturation of defogging images.
