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Cloud Removal on Satellite Image using Transfer Learning based Generative Adversarial Network
  • Ahn, Sangho ;
  • Kim, Sehyeong ;
  • Do, Jinwoo ;
  • Park, Jaehyeong ;
  • Kang, Juyoung
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Publication Year
2020-10-21
Journal
International Conference on ICT Convergence
Publisher
IEEE Computer Society
Citation
International Conference on ICT Convergence, Vol.2020-October, pp.203-205
Keyword
cloud removalgenerative adversarial networkland cover classificationsatellite image processingtransfer learning
Mesh Keyword
Adversarial networksCloud removalComplete informationGoogle earthsOptical remote sensingSatellite image datasSatellite image processingSatellite images
All Science Classification Codes (ASJC)
Information SystemsComputer Networks and Communications
Abstract
Satellite Image Processing (SIP) is important in both academic and practical aspects because it has a wide range of applications. However, since the collected Optical Remote Sensing images often contain cloudy images, it is difficult to extract complete information from satellite image data. Therefore, cloud removal from satellite imagery is important to rethink the efficiency of satellite image processing. Therefore, in this study, we propose a methodology for pre-learning the Generator based on U-net and applying Generative Adverserial Network to the satellite image data of (Cloudy, non-Cloudy) pairs collected based on Google Earth engine. This solves the quantitative problem of data that it is not easy to obtain a usable data set due to weather problems, and it will show that the pre-learning results learned from abundant data in the SIP field are effective.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36587
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85098998418&origin=inward
DOI
https://doi.org/10.1109/ictc49870.2020.9289278
Journal URL
http://ieeexplore.ieee.org/xpl/conferences.jsp
Type
Conference
Funding
This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2020-2018-0-01424) supervised by the nTP(Institute for Information & communications Technology Promotion).
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