For practical applications of X-ray ghost imaging(XGI),the imaging time is a major challenge.In this paper,we propose a fast XGI scheme based on a continuous translation mask with etched aggregate patterns.High contra...For practical applications of X-ray ghost imaging(XGI),the imaging time is a major challenge.In this paper,we propose a fast XGI scheme based on a continuous translation mask with etched aggregate patterns.High contrastto-noise ratio images are obtained with an exposure time of only 4 s and 24 s for a 3.4 mm×3.8 mm and 5.9 mm×6.1 mm field-of-view,respectively.The spatial resolution can reach∼150μm.The influences of the sampling frequency,the mask scanning speed,and the detector integration time on image quality are examined,from which we demonstrate that the imaging time can be further reduced by increasing the mask translation speed.By applying a compressed sensing reconstruction algorithm,the exposure time is greatly reduced while maintaining image quality.Our method indicates a path for the development of future XGI applications.展开更多
基金National Natural Science Foundation of China(61975229,12335016,11991073,W2412039,61805006)National Key R&D Program of China(2018YFB0504302)Strategic Priority Research Program of the CAS(XDA25030400,XDA25010100).
文摘For practical applications of X-ray ghost imaging(XGI),the imaging time is a major challenge.In this paper,we propose a fast XGI scheme based on a continuous translation mask with etched aggregate patterns.High contrastto-noise ratio images are obtained with an exposure time of only 4 s and 24 s for a 3.4 mm×3.8 mm and 5.9 mm×6.1 mm field-of-view,respectively.The spatial resolution can reach∼150μm.The influences of the sampling frequency,the mask scanning speed,and the detector integration time on image quality are examined,from which we demonstrate that the imaging time can be further reduced by increasing the mask translation speed.By applying a compressed sensing reconstruction algorithm,the exposure time is greatly reduced while maintaining image quality.Our method indicates a path for the development of future XGI applications.
