Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 5
1577-1582

Weather cloud image generation method based on SAU-NetDCGAN

Yang Pengxi1a,1b,2
Hou Jin1a,1b
You Xi1a,1b,2
Ren Dongsheng1a,1b,2
Du Maosheng1a,1b,2
1. a. IPSOM Lab, School of Information Science & Technology, b. National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 611756, China
2. Tangshan Institute, Southwest Jiaotong University, Tangshan Hebei 063000, China
DOI: 10.19734/j.issn.1001-3695.2022.08.0422

Abstract

There is a huge demand for weather cloud images in the observatory's weather monitoring system. In order to solve the problems of model instability and loss of image features when the conventional generative adversarial network expands the dataset of the weather cloud images, this paper proposed a double-layer embedded adversarial image generation method based on SAU-NetDCGAN. This method consisted of two layers of networks which were nested within each other. Firstly, by the first layer of embedded network, it added the U-shaped network to the generator of the generative adversarial network. This network acted as the basic architecture and enhanced the feature recovery capability of the image by using the jump connection between the encoder and the decoder. Secondly, by the second layer of embedded network, it added SA to the U-shaped network. This attention mechanism reduced the complexity of the model by simplifying the parameters, improved effectively the feature loss in the dark part of the image. Finally, it developed a new weight calculation method to strengthen the connection between each features and improved the extraction of detail texture features from the images. The experimental results show that the quality of the images generated by this method is better than that of the conventional generative adversarial network in terms of sharpness and saturation. The evaluation indicators PSNR and SSIM have increased by 27.06 dB and 0.606 5 respectively.

Foundation Support

国家重点研发计划资助项目(2020YFB1711902)
四川省科技计划资助项目(2020SYSY0016)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.08.0422
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 5
Section: Technology of Graphic & Image
Pages: 1577-1582
Serial Number: 1001-3695(2023)05-046-1577-06

Publish History

[2022-11-08] Accepted Paper
[2023-05-05] Printed Article

Cite This Article

杨鹏熙, 侯进, 游玺, 等. 基于SAU-NetDCGAN的天气云图生成方法 [J]. 计算机应用研究, 2023, 40 (5): 1577-1582. (Yang Pengxi, Hou Jin, You Xi, et al. Weather cloud image generation method based on SAU-NetDCGAN [J]. Application Research of Computers, 2023, 40 (5): 1577-1582. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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