Mask-based denoising scheme for ghost imaging

doi:10.1088/1674-1056/28/8/084204

Abstract Ghost imaging (GI) is thought of as a promising imaging method in many areas. However, the main drawback of GI is the huge measurement data and low signal-to-noise ratio. In this paper, we propose a novel mask-based denoising scheme to improve the reconstruction quality of GI. We first design a mask through the maximum between-class variance (OTSU) method and construct the measurement matrix with speckle patterns. Then, the correlated noise in GI can be effectively suppressed by employing the mask. From the simulation and experimental results, we can conclude that our method has the ability to improve the imaging quality compared with traditional GI method.

Keywords: ghost imaging maximum between-class variance mask image quality

Received: 22 February 2019
Revised: 09 April 2019
Accepted manuscript online:

PACS:	42.30.Va	(Image forming and processing)
	42.30.Wb	(Image reconstruction; tomography)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61627823), the Foundation for Excellent Young Talents of Jilin Province, China (Grant No. 20190103010JH), the “13th Five-Year” Science and Technology Research Project of the Education Department of Jilin Province, China (Grant No. JJKH20190277KJ), the China Postdoctoral Science Foundation (Grant No. 2018M641759), and the Fundamental Research Funds for the Central Universities, China (Grant No. 2412018QD002).

Corresponding Authors: Tian Zhang
E-mail: zhangtian114@sina.cn

Cite this article:

Yang Zhou(周阳), Shu-Xu Guo(郭树旭), Fei Zhong(钟菲), Tian Zhang(张天) Mask-based denoising scheme for ghost imaging 2019 Chin. Phys. B 28 084204

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