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CMOS Fixed Pattern Noise Removal Based on Low Rank Sparse Variational Method
Zhang T(张涛)1,2,3; Li, Xinyang1; Li, Jianfeng2; Xu Z(徐稚)3
Source PublicationAPPLIED SCIENCES-BASEL
2020-06-01
Volume10Issue:11Pages:26
DOI10.3390/app10113694
Contribution Rank第3完成单位
Indexed BySCI
KeywordFPN low rank sparse total variation anisotropy characteristic
Abstract

Fixed pattern noise (FPN) has always been an important factor affecting the imaging quality of CMOS image sensor (CIS). However, the current scene-based FPN removal methods mostly focus on the image itself, and seldom consider the structure information of the FPN, resulting in various undesirable noise removal effects. This paper presents a scene-based FPN correction method: the low rank sparse variational method (LRSUTV). It combines not only the continuity of the image itself, but also the structural and statistical characteristics of the stripes. At the same time, the low frequency information of the image is combined to achieve adaptive adjustment of some parameters, which simplifies the process of parameter adjustment, to a certain extent. With the help of adaptive parameter adjustment strategy, LRSUTV shows good performance under different intensity of stripe noise, and has high robustness.

Funding ProjectNational Natural Science Foundation of China[11573066] ; National Natural Science Foundation of China[11873091] ; Yunnan Province Basic Research Plan[2019FA001]
Funding OrganizationNational Natural Science Foundation of China[11573066, 11873091] ; Yunnan Province Basic Research Plan[2019FA001]
Language英语
Subject Area电子、通信与自动控制技术
MOST Discipline Catalogue工学 ; 工学::电子科学与技术(可授工学、理学学位)
SubtypeArticle
PublisherMDPI
Publication PlaceST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND
URL查看原文
WOS IDWOS:000543385900031
WOS Research AreaChemistry ; Engineering ; Materials Science ; Physics
WOS SubjectChemistry, Multidisciplinary ; Engineering, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS KeywordREMOTE-SENSING IMAGES ; WAVELET
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ynao.ac.cn/handle/114a53/23539
Collection抚仙湖太阳观测站
Corresponding AuthorZhang T(张涛)
Affiliation1.Key Laboratory of Adaptive Optics, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
2.School of Optoelectronic Information, University of Electronic Science and Technology, Chengdu 611731, China
3.Astronomical Technology Laboratory, Yunnan Observatory, Chinese Academy of Sciences, Kunming 650216, China
First Author AffilicationYunnan Observatories, Chinese Academy of Sciences
Corresponding Author AffilicationYunnan Observatories, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang T,Li, Xinyang,Li, Jianfeng,et al. CMOS Fixed Pattern Noise Removal Based on Low Rank Sparse Variational Method[J]. APPLIED SCIENCES-BASEL,2020,10(11):26.
APA Zhang T,Li, Xinyang,Li, Jianfeng,&Xu Z.(2020).CMOS Fixed Pattern Noise Removal Based on Low Rank Sparse Variational Method.APPLIED SCIENCES-BASEL,10(11),26.
MLA Zhang T,et al."CMOS Fixed Pattern Noise Removal Based on Low Rank Sparse Variational Method".APPLIED SCIENCES-BASEL 10.11(2020):26.
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