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.
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页数：4
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