Laser & Optoelectronics Progress, Volume. 58, Issue 4, 0410013(2021)
Image Super-Resolution Reconstruction Method Based on Self-Attention Deep Network
Fig. 3. Plane images reconstructed by different methods. (a) Low-resolution input image with enlarged display; (b) Bicubic; (c) SRCNN; (d) FSRCNN; (e) SADeepNet; (f) high-resolution original image
Fig. 4. Chair images reconstructed by different methods. (a) Low-resolution input image with enlarged display; (b) Bicubic; (c) SRCNN; (d) FSRCNN; (e) SADeepNet; (f) high-resolution original image
Fig. 5. Butterfly images reconstructed by different methods. (a) Low-resolution input image with enlarged display; (b) Bicubic; (c) SRCNN; (d) FSRCNN; (e) SADeepNet; (f) high-resolution original image
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Zihan Chen, Haobo Wu, Haodong Pei, Rong Chen, Jiaxin Hu, Hengtong Shi. Image Super-Resolution Reconstruction Method Based on Self-Attention Deep Network[J]. Laser & Optoelectronics Progress, 2021, 58(4): 0410013
Category: Image Processing
Received: Jun. 30, 2020
Accepted: Aug. 7, 2020
Published Online: Feb. 25, 2021
The Author Email: Wu Haobo (haobow@126.com), Pei Haodong (haobow@126.com)