中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Dual-Path Adversarial Generation Network for Super-Resolution Reconstruction of Remote Sensing Images

文献类型:期刊论文

作者Z. P. Ren, J. P. Zhao, C. Y. Chen, Y. Lou and X. C. Ma
刊名Applied Sciences-Basel
出版日期2023
卷号13期号:3页码:15
DOI10.3390/app13031245
英文摘要Satellite remote sensing images contain adequate ground object information, making them distinguishable from natural images. Due to the constraint hardware capability of the satellite remote sensing imaging system, coupled with the surrounding complex electromagnetic noise, harsh natural environment, and other factors, the quality of the acquired image may not be ideal for follow-up research to make suitable judgment. In order to obtain clearer images, we propose a dual-path adversarial generation network model algorithm that particularly improves the accuracy of the satellite remote sensing image super-resolution. This network involves a dual-path convolution operation in a generator structure, a feature mapping attention mechanism that first extracts important feature information from a low-resolution image, and an enhanced deep convolutional network to extract the deep feature information of the image. The deep feature information and the important feature information are then fused in the reconstruction layer. Furthermore, we also improve the algorithm structure of the loss function and discriminator to achieve a relatively optimal balance between the output image and the discriminator, so as to restore the super-resolution image closer to human perception. Our algorithm was validated on the public UCAS-AOD datasets, and the obtained results showed significantly improved performance compared to other methods, thus exhibiting a real advantage in supporting various image-related field applications such as navigation monitoring.
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语种英语
源URL[http://ir.ciomp.ac.cn/handle/181722/67817]  
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
Z. P. Ren, J. P. Zhao, C. Y. Chen, Y. Lou and X. C. Ma. Dual-Path Adversarial Generation Network for Super-Resolution Reconstruction of Remote Sensing Images[J]. Applied Sciences-Basel,2023,13(3):15.
APA Z. P. Ren, J. P. Zhao, C. Y. Chen, Y. Lou and X. C. Ma.(2023).Dual-Path Adversarial Generation Network for Super-Resolution Reconstruction of Remote Sensing Images.Applied Sciences-Basel,13(3),15.
MLA Z. P. Ren, J. P. Zhao, C. Y. Chen, Y. Lou and X. C. Ma."Dual-Path Adversarial Generation Network for Super-Resolution Reconstruction of Remote Sensing Images".Applied Sciences-Basel 13.3(2023):15.

入库方式: OAI收割

来源:长春光学精密机械与物理研究所

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