Optics and Precision Engineering, Volume. 30, Issue 17, 2155(2022)
Super-resolution reconstruction method for space target images based on dense residual block-based GAN
Fig. 1. Framework of residual in residual dense block GAN generator network
Fig. 6. Comparison of super-resolution results of AO images from Hubble Telescope 1((a) is a low-resolution simulation adaptive optical image whose original input is 256×256, and (b)-(e) are 1 024×1 024 super resolution image network)
Fig. 7. Comparison of super-resolution results of AO images from sat1 Satellite((a) is a low-resolution simulation adaptive optical image whose original input is 256×256, and (b)-(e) are 1 024×1 024 super resolution image network)
Fig. 8. Comparison of super-resolution results of AO images from Hubble Telescope 2((a) is a low-resolution simulation adaptive optical image whose original input is 256×256, and (b)-(e) are 1 024×1 024 super resolution image network)
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Haizhao JING, Jianglin SHI, Mengzhe QIU, Yong QI, Wenxiao ZHU. Super-resolution reconstruction method for space target images based on dense residual block-based GAN[J]. Optics and Precision Engineering, 2022, 30(17): 2155
Category: Information Sciences
Received: Jun. 7, 2022
Accepted: --
Published Online: Oct. 20, 2022
The Author Email: Jianglin SHI (shijianglin89@163.com)