Superresolution Imaging With a Deep Multipath Network for the Reconstruction of Satellite Cloud Images-Reference-Cited by-同舟云学术

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Superresolution Imaging With a Deep Multipath Network for the Reconstruction of Satellite Cloud Images

Published:2021-06 Issue:6 Volume:8 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth Space Sci

Author:

Zhang Jinglin¹²^ORCID,Yang Zhipeng¹^ORCID,Jia Zhaoying¹,Bai Cong³^ORCID

Affiliation:

1. Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University of Information Science and Technology Nanjing China

2. School of Computer and Software Nanjing University of Information Science and Technology Nanjing China

3. College of Computer Science and Technology Zhejiang University of Technology Hangzhou China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Priority Academic Program Development of Jiangsu Higher Education Institutions

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020EA001559

Reference26 articles.

1. An exploratory study of cloud remote sensing capabilities of the Communication, Ocean and Meteorological Satellite (COMS) imagery

2. Image Super-Resolution Using Deep Convolutional Networks

3. Estimation of 2006 Northern Hemisphere contrail coverage using MODIS data

4. Garg A. Naidu S. V. Ahmed T. Yahia H. &Singh D.(2014). Wavelet based resolution enhancement for low resolution satellite images. In 20149th International Conference on Industrial and Information Systems (ICIIS)(pp. 1–5).

5. Haris M. Shakhnarovich G. &Ukita N.(2018). Deep back‐projection networks for super‐resolution. InProceedings of the IEEE Conference on Computer Vision and Pattern Recognition(pp. 1664–1673).

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