典型文献
Image Desaturation for SDO/AIA Using Mixed Convolution Network
文献摘要：
The Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) provides full-disk solar images with high temporal cadence and spatial resolution over seven extreme ultraviolet (EUV) wave bands. However, as violent solar flares happen, images captured in EUV wave bands may have saturation in active regions, resulting in signal loss. In this paper, we propose a deep learning model to restore the lost signal in saturated regions by referring to both unsaturated/normal regions within a solar image and statistical probability model of massive normal solar images. The proposed model, namely mixed convolution network (MCNet), is established over conditional generative adversarial network (GAN) and the combination of partial convolution (PC) and validness migratable convolution (VMC). These two convolutions were originally proposed for image inpainting. In addition, they are implemented only on unsaturated/valid pixels, followed by certain compensation to compensate the deviation of PC/VMC relative to normal convolution. Experimental results demonstrate that the proposed MCNet achieves favorable desaturated results for solar images and outperforms the state-of-the-art methods both quantitatively and qualitatively.
文献关键词：
中图分类号：
作者姓名：
Xuexin Yu;Long Xu;Zhixiang Ren;Dong Zhao;Wenqing Sun
作者机构：
National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China;Peng Cheng National Laboratory,Shenzhen 518000,China;National Space Science Center,Chinese Academy of Sciences,Beijing 100190,China;State Key Laboratory of Virtual Reality Technology and Systems,School of Computer Science and Engineering,Beihang University,Beijing 100191,China
文献出处：
引用格式：
[1]Xuexin Yu;Long Xu;Zhixiang Ren;Dong Zhao;Wenqing Sun-.Image Desaturation for SDO/AIA Using Mixed Convolution Network)[J].天文和天体物理学研究,2022(06):91-100
A类：
Desaturation,MCNet,validness,migratable,desaturated
B类：
Image,SDO,AIA,Using,Mixed,Convolution,Network,Atmospheric,Imaging,Assembly,onboard,Solar,Dynamics,Observatory,provides,full,disk,solar,images,high,temporal,cadence,spatial,resolution,over,seven,extreme,ultraviolet,EUV,wave,bands,However,violent,flares,happen,captured,may,have,active,regions,resulting,signal,loss,In,this,paper,deep,learning,model,restore,lost,by,referring,both,unsaturated,normal,within,statistical,probability,massive,proposed,namely,mixed,network,established,conditional,generative,adversarial,GAN,combination,partial,VMC,These,convolutions,were,originally,inpainting,addition,they,implemented,only,pixels,followed,certain,compensation,compensate,deviation,relative,Experimental,results,demonstrate,that,achieves,favorable,outperforms,state,methods,quantitatively,qualitatively
AB值：
0.590247
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
