Ghost Imaging by a Proportional Parameter to Filter Bucket Data

Most ghost imaging reconstruction algorithms require a large measurement time to retrieve the object information clearly. But not all groups of data play a positive role in reconstructing the object image. Abandoning some redundant data can not only enhance the quality of reconstruction images but a...

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Bibliographic Details
Main Authors: Min Tao, Xiaobin Gong, Jian Guan, Junfeng Song, Zhixin Song, Xueyan Li, Shuxu Guo, Jian Chen, Siyao Yu, Fengli Gao
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/11/1/227
Description
Summary:Most ghost imaging reconstruction algorithms require a large measurement time to retrieve the object information clearly. But not all groups of data play a positive role in reconstructing the object image. Abandoning some redundant data can not only enhance the quality of reconstruction images but also speed up the computation process. Here, we propose a method to screen the data using two threshold values set by a proportional parameter during the sampling process. Experimental results show that the reserved data after screening can be used in several reconstruction algorithms, and the reconstruction quality is enhanced or at least remains at the same level. Meanwhile, the computing time costs are greatly reduced, and so is the data storage.
ISSN:2076-3417