TY -的A2 Musielak Zdzislaw e . AU -赵ng AU - Xu, Long AU - Chen, Linjie AU - Yan, Yihua AU - Duan, Ling-Yu PY - 2019 DA - 2019/09/05 TI - Mask-Pix2Pix Network for Overexposure Region Recovery of Solar Image SP - 5343254 VL - 2019 AB - 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. SN - 1687-7969 UR - https://doi.org/10.1155/2019/5343254 DO - 10.1155/2019/5343254 JF - Advances in Astronomy PB - Hindawi KW - ER -