Spectral bandwidth correction with optimal parameters based on deep learning

doi:10.1364/AO.412526

HFCAS OpenIR

	Spectral bandwidth correction with optimal parameters based on deep learning
	Cui, Hao 1,2,3; Xia, Guo 1,2,3; Huang, Chan 4; Wang, Jiangtao 1,2,3; Bai, Lihao 1,2,3
	2021-02-10
发表期刊	APPLIED OPTICS
ISSN	1559-128X
通讯作者	Xia, Guo(xiaguo@hfut.edu.cn)
摘要	Spectral bandwidth correction is an effective way to obtain the original spectrum. However, the correct selection of optimal parameters used to recover the distortion spectrum in bandwidth correction algorithms has always been an important problem. To overcome the shortcomings of traditional parameter selection methods and obtain the optimal parameter, we propose a new optimal parameter selection method based on deep learning (DL). First, the database and neural network were constructed, and then the optimal parameters of corresponding algorithms were obtained through the training of the neural network. In order to verify the superiority of the optimal parameter selection method based on DL, the Levenberg-Marquardt (L-M) and Richardson-Lucy (R-L) algorithms with corresponding optimal parameters were compared with the traditional L-M and R-L algorithms to recover the distortion white light-emitting diode, Raman spectrum, and compact fluorescent lamp spectrum. The type A uncertainty and root mean square error values of the different cases were calculated. The results proved that, compared with the traditional methods for obtaining the optimal parameters, the neural network was capable of obtaining parameters that can make the bandwidth correction algorithm more efficient at recovering the distorted spectrum. (C) 2021 Optical Society of America
DOI	10.1364/AO.412526
关键词[WOS]	ALGORITHM ; SPECTROMETER ; DECONVOLUTION
收录类别	SCI
语种	英语
资助项目	Key Research and Development Program of Anhui Province[1804d08020310]
项目资助者	Key Research and Development Program of Anhui Province
WOS研究方向	Optics
WOS类目	Optics
WOS记录号	WOS:000617545500027
出版者	OPTICAL SOC AMER
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.hfcas.ac.cn:8080/handle/334002/120488
专题	中国科学院合肥物质科学研究院
通讯作者	Xia, Guo
作者单位	1.Hefei Univ Technol, Acad Optoelect Technol, Hefei, Peoples R China 2.Special Display & Imaging Technol Innovat Ctr Anh, Hefei, Peoples R China 3.State Key Lab Adv Display Technol, Hefei, Peoples R China 4.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei 230031, Anhui, Peoples R China
推荐引用方式 GB/T 7714	Cui, Hao,Xia, Guo,Huang, Chan,et al. Spectral bandwidth correction with optimal parameters based on deep learning[J]. APPLIED OPTICS,2021,60.
APA	Cui, Hao,Xia, Guo,Huang, Chan,Wang, Jiangtao,&Bai, Lihao.(2021).Spectral bandwidth correction with optimal parameters based on deep learning.APPLIED OPTICS,60.
MLA	Cui, Hao,et al."Spectral bandwidth correction with optimal parameters based on deep learning".APPLIED OPTICS 60(2021).