Mask-Pix2Pix Network for Overexposure Region Recovery of Solar Image
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Overexposure may happen for imaging of solar observation as extremely violet solar bursts occur, which means that signal intensity goes beyond the dynamic range of imaging system of a telescope, resulting in loss of signal.
For example, during solar flare, Atmospheric Imaging Assembly (AIA) of Solar Dynamics Observatory (SDO) often records overexposed images/videos, resulting loss of fine structures of solar flare.
This paper makes effort to retrieve/recover missing information of overexposure by exploiting deep learning for its powerful nonlinear representation which makes it widely used in image reconstruction/restoration.
First, a new model, namely, mask-Pix2Pix network, is proposed for overexposure recovery.
It is built on a well-known Pix2Pix network of conditional generative adversarial network (cGAN).
In addition, a hybrid loss function, including an adversarial loss, a masked L1 loss and a edge mass loss/smoothness, are integrated together for addressing challenges of overexposure relative to conventional image restoration.
Moreover, a new database of overexposure is established for training the proposed model.
Extensive experimental results demonstrate that the proposed mask-Pix2Pix network can well recover missing information of overexposure and outperforms the state of the arts originally designed for image reconstruction tasks.
American Psychological Association (APA)
Zhao, Dong& Xu, Long& Chen, Linjie& Yan, Yihua& Duan, Ling-Yu. 2019. Mask-Pix2Pix Network for Overexposure Region Recovery of Solar Image. Advances in Astronomy،Vol. 2019, no. 2019, pp.1-10.
Modern Language Association (MLA)
Zhao, Dong…[et al.]. Mask-Pix2Pix Network for Overexposure Region Recovery of Solar Image. Advances in Astronomy No. 2019 (2019), pp.1-10.
American Medical Association (AMA)
Zhao, Dong& Xu, Long& Chen, Linjie& Yan, Yihua& Duan, Ling-Yu. Mask-Pix2Pix Network for Overexposure Region Recovery of Solar Image. Advances in Astronomy. 2019. Vol. 2019, no. 2019, pp.1-10.
Includes bibliographical references
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