Fringe removal algorithms for atomic absorption images: A survey

doi:10.1088/1674-1056/ac3758

中国物理B ›› 2022, Vol. 31 ›› Issue (5): 50313-050313.doi: 10.1088/1674-1056/ac3758

Fringe removal algorithms for atomic absorption images: A survey

Gaoyi Lei(雷高益)¹, Chencheng Tang(唐陈成)^2,†, and Yueyang Zhai(翟跃阳)^3,‡

1 School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China;
2 Quantum Sensing Center, Zhejiang Laboratory, Hangzhou 310000, China;
3 Research Institute of Frontier Science, Beihang University, Beijing 100191, China

收稿日期:2021-09-01 修回日期:2021-10-18 发布日期:2022-04-29
通讯作者: Chencheng Tang,E-mail:tangchencheng@zhejianglab.com;Yueyang Zhai,E-mail:yueyangzhai@buaa.edu.cnn E-mail:tangchencheng@zhejianglab.com;yueyangzhai@buaa.edu.cnn
基金资助:
This research was founded by the National Natural Science Foundation of China (Grant No.62003020).

Fringe removal algorithms for atomic absorption images: A survey

Gaoyi Lei(雷高益)¹, Chencheng Tang(唐陈成)^2,†, and Yueyang Zhai(翟跃阳)^3,‡

1 School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China;
2 Quantum Sensing Center, Zhejiang Laboratory, Hangzhou 310000, China;
3 Research Institute of Frontier Science, Beihang University, Beijing 100191, China

Received:2021-09-01 Revised:2021-10-18 Published:2022-04-29
Contact: Chencheng Tang,E-mail:tangchencheng@zhejianglab.com;Yueyang Zhai,E-mail:yueyangzhai@buaa.edu.cnn E-mail:tangchencheng@zhejianglab.com;yueyangzhai@buaa.edu.cnn
About author:2021-11-8
Supported by:
This research was founded by the National Natural Science Foundation of China (Grant No.62003020).

摘要/Abstract

摘要： The fringe noises disrupt the precise measurement of the atom distribution in the process of the absorption images. The fringe removal algorithms have been proposed to reconstruct the ideal reference images of the absorption images to remove the fringe noises. However, the focus of these fringe removal algorithms is the association of the fringe removal performance with the physical systems, leaving the gap to analyze the workflows of different fringe removal algorithms. This survey reviews the fringe removal algorithms and classifies them into two categories: the image-decomposition based methods and the deep-learning based methods. Then this survey draws the workflow details of two classical fringe removal algorithms, and conducts experiments on the absDL ultracold image dataset. Experiments show that the singular value decomposition (SVD) method achieves outstanding performance, and the U-net method succeeds in implying the image inpainting idea. The main contribution of this survey is the interpretation of the fringe removal algorithms, which may help readers have a better understanding of the research status. Codes in this survey are available at https://github.com/leigaoyi/Atomic_Fringe_Denoise.

关键词: atomic absorption image, fringe removal, principal component analysis, deep learning

Abstract: The fringe noises disrupt the precise measurement of the atom distribution in the process of the absorption images. The fringe removal algorithms have been proposed to reconstruct the ideal reference images of the absorption images to remove the fringe noises. However, the focus of these fringe removal algorithms is the association of the fringe removal performance with the physical systems, leaving the gap to analyze the workflows of different fringe removal algorithms. This survey reviews the fringe removal algorithms and classifies them into two categories: the image-decomposition based methods and the deep-learning based methods. Then this survey draws the workflow details of two classical fringe removal algorithms, and conducts experiments on the absDL ultracold image dataset. Experiments show that the singular value decomposition (SVD) method achieves outstanding performance, and the U-net method succeeds in implying the image inpainting idea. The main contribution of this survey is the interpretation of the fringe removal algorithms, which may help readers have a better understanding of the research status. Codes in this survey are available at https://github.com/leigaoyi/Atomic_Fringe_Denoise.

Key words: atomic absorption image, fringe removal, principal component analysis, deep learning

中图分类号:

03.75.-b

03.75.Be (Atom and neutron optics) 67.85.-d (Ultracold gases, trapped gases)

Gaoyi Lei(雷高益), Chencheng Tang(唐陈成), and Yueyang Zhai(翟跃阳). Fringe removal algorithms for atomic absorption images: A survey[J]. 中国物理B, 2022, 31(5): 50313-050313.

Gaoyi Lei(雷高益), Chencheng Tang(唐陈成), and Yueyang Zhai(翟跃阳). Fringe removal algorithms for atomic absorption images: A survey[J]. Chin. Phys. B, 2022, 31(5): 50313-050313.

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Fringe removal algorithms for atomic absorption images: A survey

Fringe removal algorithms for atomic absorption images: A survey

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