Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm
Haipeng Zhang(张海鹏)1,2,3, Ke Li(李可)2, Changzhe Zhao(赵昌哲)1,2,3, Jie Tang(汤杰), and Tiqiao Xiao(肖体乔)1,2,3,†
1 Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China; 2 Shanghai Synchrotron Radiation Facility/Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201204, China; 3 University of Chinese Academy of Sciences, Beijing 100049, China
Abstract Towards efficient implementation of x-ray ghost imaging (XGI), efficient data acquisition and fast image reconstruction together with high image quality are preferred. In view of radiation dose resulted from the incident x-rays, fewer measurements with sufficient signal-to-noise ratio (SNR) are always anticipated. Available methods based on linear and compressive sensing algorithms cannot meet all the requirements simultaneously. In this paper, a method based on a modified compressive sensing algorithm with conjugate gradient descent method (CGDGI) is developed to solve the problems encountered in available XGI methods. Simulation and experiments demonstrate the practicability of CGDGI-based method for the efficient implementation of XGI. The image reconstruction time of sub-second implicates that the proposed method has the potential for real-time XGI.
Fund: Project supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0206004,2017YFA0206002, 2018YFC0206002, and 2017YFA0403801) and National Natural Science Foundation of China (Grant No. 81430087).
Haipeng Zhang(张海鹏), Ke Li(李可), Changzhe Zhao(赵昌哲), Jie Tang(汤杰), and Tiqiao Xiao(肖体乔) Efficient implementation of x-ray ghost imaging based on a modified compressive sensing algorithm 2022 Chin. Phys. B 31 064202
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