Characterization and digital aberration correction of a hyperspectral imaging system for plant disease detection

被引：1

作者：

Zabic, Miroslav ^{[1
,2
]}

Jose, Lijin ^{[1
]}

Landes, Timm ^{[1
,2
,3
]}

Fritz, Jan-Michael ^{[1
,2
]}

Weisheit, Inga ^{[1
,2
]}

Heinemann, Dag ^{[1
,2
,3
]}

机构：

[1] Leibniz Univ Hannover, Hannover Ctr Opt Technol HOT, Nienburger Str 17, D-30167 Hannover, Germany

[2] Leibniz Univ Hannover, Inst Hort Prod Syst, Herrenhauser Str 2, D-30419 Hannover, Germany

[3] Leibniz Univ Hannover, PhoenixD Cluster Excellence, Welfengarten 1A, D-30167 Hannover, Germany

来源：

PHOTONIC INSTRUMENTATION ENGINEERING X | 2023年 / 12428卷

关键词：

hyperspectral imaging; spatial resolution; deconvolution; plant disease detection; agriculture;

D O I：

10.1117/12.2647833

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Hyperspectral imaging is a key technology for monitoring agricultural crops and vegetation. It can be used for health estimation and the early detection of disease symptoms in plants. This can help to reduce the use of pesticides by allowing targeted and early intervention. Cost-efficient hyperspectral imaging systems are necessary to meet the increasing demand for monitoring techniques for agricultural products. These systems usually suffer from sub-optimal image quality. Here we present a digital aberration correction for hyperspectral image data.

引用

页数：4

共 50 条

[1] Plant Disease Detection using Hyperspectral Imaging
Moghadam, Peyman
Ward, Daniel
Goan, Ethan
Jayawardena, Srimal
Sikka, Pavan
Hernandez, Emili
2017 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING - TECHNIQUES AND APPLICATIONS (DICTA), 2017, : 384 - 391
[2] A Review on Plant Disease Detection Using Hyperspectral Imaging
Rayhana, Rakiba
Ma, Zhenyu
Liu, Zheng
Xiao, Gaozhi
Ruan, Yuefeng
Sangha, Jatinder S.
IEEE Transactions on AgriFood Electronics, 2023, 1 (02): : 108 - 134
[3] Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective
Stefan Thomas
Matheus Thomas Kuska
David Bohnenkamp
Anna Brugger
Elias Alisaac
Mirwaes Wahabzada
Jan Behmann
Anne-Katrin Mahlein
Journal of Plant Diseases and Protection, 2018, 125 : 5 - 20
[4] Benefits of hyperspectral imaging for plant disease detection and plant protection: a technical perspective
Thomas, Stefan
Kuska, Matheus Thomas
Bohnenkamp, David
Brugger, Anna
Alisaac, Elias
Wahabzada, Mirwaes
Behmann, Jan
Mahlein, Anne-Katrin
JOURNAL OF PLANT DISEASES AND PROTECTION, 2018, 125 (01) : 5 - 20
[5] Digital aberration correction for in-vivo retinal OCT imaging
Leitgeb, Rainer A.
Ginner, Laurin
Kumar, Abhishek
Fechtig, Daniel
2016 15TH WORKSHOP ON INFORMATION OPTICS (WIO), 2016,
[6] Early Detection of Plant Viral Disease Using Hyperspectral Imaging and Deep Learning
Nguyen, Canh
Sagan, Vasit
Maimaitiyiming, Matthew
Maimaitijiang, Maitiniyazi
Bhadra, Sourav
Kwasniewski, Misha T.
SENSORS, 2021, 21 (03) : 1 - 23
[7] Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging
Bock, C. H.
Poole, G. H.
Parker, P. E.
Gottwald, T. R.
CRITICAL REVIEWS IN PLANT SCIENCES, 2010, 29 (02) : 59 - 107
[8] Computational aberration correction for an arbitrary linear imaging system
Allen, LJ
Oxley, MP
Paganin, D
PHYSICAL REVIEW LETTERS, 2001, 87 (12) : 1 - 123902
[9] Aberration correction method for the catadioptric imaging system design
Liu, Zhenjie
Yu, Feihong
APPLIED OPTICS, 2016, 55 (11) : 2943 - 2950
[10] Illumination system characterization for hyperspectral imaging
Katrasnik, Jaka
Pernus, Franjo
Likar, Bostjan
DESIGN AND QUALITY FOR BIOMEDICAL TECHNOLOGIES IV, 2011, 7891

← 1 2 3 4 5 →