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Open AccessArticle

Remote Sensing Single-Image Resolution Improvement Using A Deep Gradient-Aware Network with Image-Specific Enhancement

1
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
2
Aix Marseille Univ, Université de Toulon, CNRS, LIS, Marseille 13001, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(5), 758; https://doi.org/10.3390/rs12050758
Received: 29 December 2019 / Revised: 21 February 2020 / Accepted: 21 February 2020 / Published: 26 February 2020
Super-resolution (SR) is able to improve the spatial resolution of remote sensing images, which is critical for many practical applications such as fine urban monitoring. In this paper, a new single-image SR method, deep gradient-aware network with image-specific enhancement (DGANet-ISE) was proposed to improve the spatial resolution of remote sensing images. First, DGANet was proposed to model the complex relationship between low- and high-resolution images. A new gradient-aware loss was designed in the training phase to preserve more gradient details in super-resolved remote sensing images. Then, the ISE approach was proposed in the testing phase to further improve the SR performance. By using the specific features of each test image, ISE can further boost the generalization capability and adaptability of our method on inexperienced datasets. Finally, three datasets were used to verify the effectiveness of our method. The results indicate that DGANet-ISE outperforms the other 14 methods in the remote sensing image SR, and the cross-database test results demonstrate that our method exhibits satisfactory generalization performance in adapting to new data. View Full-Text
Keywords: super-resolution; CNN; remote sensing; deep gradient-aware network; image-specific enhancement super-resolution; CNN; remote sensing; deep gradient-aware network; image-specific enhancement
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MDPI and ACS Style

Qin, M.; Mavromatis, S.; Hu, L.; Zhang, F.; Liu, R.; Sequeira, J.; Du, Z. Remote Sensing Single-Image Resolution Improvement Using A Deep Gradient-Aware Network with Image-Specific Enhancement. Remote Sens. 2020, 12, 758. https://doi.org/10.3390/rs12050758

AMA Style

Qin M, Mavromatis S, Hu L, Zhang F, Liu R, Sequeira J, Du Z. Remote Sensing Single-Image Resolution Improvement Using A Deep Gradient-Aware Network with Image-Specific Enhancement. Remote Sensing. 2020; 12(5):758. https://doi.org/10.3390/rs12050758

Chicago/Turabian Style

Qin, Mengjiao; Mavromatis, Sébastien; Hu, Linshu; Zhang, Feng; Liu, Renyi; Sequeira, Jean; Du, Zhenhong. 2020. "Remote Sensing Single-Image Resolution Improvement Using A Deep Gradient-Aware Network with Image-Specific Enhancement" Remote Sens. 12, no. 5: 758. https://doi.org/10.3390/rs12050758

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