Impact of Satellite Sounding Data on Virtual Visible Imagery Generation Using Conditional Generative Adversarial Network

Impact of Satellite Sounding Data on Virtual Visible Imagery Generation Using Conditional Generative Adversarial Network

The visible band of satellite sensors is of limited use during the night due to a lack of solar reflection. This study presents an improved conditional generative adversarial networks (CGANs) model to generate virtual nighttime visible imagery using infrared (IR) multiband satellite observations and...

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Bibliographic Details
Main Authors: Ji-Hye Kim, Sumin Ryu, Jaehoon Jeong, Damwon So, Hyun-Ju Ban, Sungwook Hong
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Clouds
conditional generative adversarial network (CGAN)
deep learning
multiband
nighttime
typhoon
Online Access:https://ieeexplore.ieee.org/document/9154540/

Internet

https://ieeexplore.ieee.org/document/9154540/

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