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2022 | OriginalPaper | Chapter

5. Deep Learning in Solar Image Generation Tasks

Authors : Long Xu, Yihua Yan, Xin Huang

Published in: Deep Learning in Solar Astronomy

Publisher: Springer Nature Singapore

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Abstract

It has been witnessed that deep learning has been applied to classification in previous chapters. In fact, deep learning also demonstrated great ability of image generation which is more challenging than classification. In this chapter, several applications of deep learning in solar image enhancement, reconstruction and processing are presented, including image deconvolution of solar radioheliograph, desaturation of solar imaging, generating magnetogram, image super-resolution. These tasks are all concerned with image generation, by employing generative neural networks. As a representative of generative networks, GAN was widely exploited in image generation tasks. It can generate high fidelity and photo-realistic content mainly owning to an adversarial loss.

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Metadata
Title
Deep Learning in Solar Image Generation Tasks
Authors
Long Xu
Yihua Yan
Xin Huang
Copyright Year
2022
Publisher
Springer Nature Singapore
Book
Deep Learning in Solar Astronomy

Print ISBN: 978-981-19-2745-4

Electronic ISBN: 978-981-19-2746-1

Copyright Year: 2022

DOI
https://doi.org/10.1007/978-981-19-2746-1_5

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