Image dehazing algorithm based on ViTGAN and its application

In recent years, many methods based on deep learning have emerged in the field of image dehazing. The ViTGAN generation adversarial network based on Transformer is used to design image dehazing algorithm.In ViTGAN, the generator is improved to achieve the desired effect.The first half of the collate...

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Bibliographic Details
Published in:Journal of physics. Conference series 2023-02, Vol.2425 (1), p.12004
Main Author: Liu, Jianghao
Format: Article
Language:English
Subjects:
Algorithms
Coders
Density
Feature extraction
Feature maps
Machine learning
Physics
Sampling
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Summary:In recent years, many methods based on deep learning have emerged in the field of image dehazing. The ViTGAN generation adversarial network based on Transformer is used to design image dehazing algorithm.In ViTGAN, the generator is improved to achieve the desired effect.The first half of the collaterals can be used as a data encoder to extract the features of the original image. In this part, a lower sampling layer is placed behind each density block.Generate network can regard as the second half of a corresponding to the first encoder decoder, in this part, each layer of the sampling density behind block placed a, for the first half is passed on the image characteristics of sampling, can be reduced by the sampling image characteristics to enlarge to the image of the original size, to ensure that the network output is correct.The feature map of the decoder and the symmetric encoder can be fused to ensure that the features of the decoder can be properly represented.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/2425/1/012004