Journal of Astronautics ›› 2021, Vol. 42 ›› Issue (9): 1172-1177.doi: 10.3873/j.issn.1000-1328.2021.09.012

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Turbulence Free Near Infrared Computational Ghost Imaging

YANG Zhao hua, CHEN Xiang, LI Ming fei, YU Yuan jin   

  1. 1. School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China;2. School of Automation and Electrical Engineering, Beihang University, Beijing 100191, China;3. Beijing Institute of Aerospace Control Devices, Beijing 100039, China;4.School of Automation,Beijing Institute of Technology, Beijing 100081, China

  • Received:2020-10-19 Revised:2021-02-02 Online:2021-09-15 Published:2021-09-15

Abstract: As traditional optical imaging is seriously affected by the atmospheric turbulence, a turbulence free near infrared computational ghost imaging method is proposed to improve the imaging quality. Computational ghost imaging gets the image information by correlating the modulated light field and the total intensity of light that is transmitted or reflected by the object, where the modulated light field is one of the major factors affecting the imaging quality. Due to the turbulence changes with time and space, it is treated as a randomly modulated light field in this work. We use the power spectrum inversion to simulate the influence of phase disturbance caused by three different atmospheric turbulence intensities (strong, medium and weak), and add the turbulences to the optical propagation path. Finally, a near infrared camera is used as the detector to realize the computational ghost imaging. The results of simulations show that the peak signal to noise ratio of the reconstructed images under three different intensity turbulence conditions are 19.4 dB, 24.2 dB and 64.58 dB, respectively. The results demonstrate the effectiveness of the computational ghost imaging against atmospheric turbulence in the near infrared band. The proposed method is simple in structure and easy to be implemented, which provides a technical approach for near infrared turbulence free detection.

Key words: Near infrared detection, Computational ghost imaging, Turbulence free, Power spectrum inversion

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