摘要
天线接收到天体的频域值,经傅里叶逆变换得到了天体的亮度分布图。由于天文观测站天线数量有限,只能接收到部分的频域数据,为了达到更好的视觉效果,对天体亮度分布图进行图像恢复。在数学上,天文图像恢复主要处理欠采样样本的还原,采用洁化算法与最大熵方法来进行处理,两种方法未从根本上解决欠采样样本的还原问题。通过基于压缩感知理论与最大熵方法相结合的方法对欠采样的射电太阳图像进行恢复,得到了不错的效果。
By Fourier inverse transform,frequency domain value of celestial body received by antenna gets luminance distribution map of celestial. However,due to the limited number of antennas in the astronomical observatory,only partial data of frequency domain can be received. In order to achieve better visual effects,image restoration for brightness distribution map of astronomical objects is needed. In mathematics,astronomical image restoration is mainly aimed at dealing with the reduction process of undersampled samples.Use cleaning algorithm and the maximum entropy method to process.But these two methods do not fundamentally solve the problem of the reduction of the undersampled sample. The method combining the compressed sensing theory and the maximum entropy method is used to restore the radio solar image under the under sampling,and the effect is good.
作者
卫明
袁梅宇
张秋明
王赟
WEI Ming;YUAN Mei-yu;ZHANG Qiu-ming;WANG Yun(Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650000, China;Yangquan High-tech Innovation Service Center, Yangquan 045000, China)
出处
《传感器与微系统》
CSCD
2018年第4期54-57,61,共5页
Transducer and Microsystem Technologies
基金
国家火炬计划产业化环境建设项目(2015GH511343)
关键词
射电天文图像
信号采样
压缩感知
最大熵
压缩感知与最大熵相结合
radio astronomical images
signal sampling
compressed sensing
maximum entropy
compressedsensing and maximum entropy
