Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Photonic Instrumentation Engineering X |
| Herausgeber/-innen | Lynda E. Busse, Yakov Soskind |
| Herausgeber (Verlag) | SPIE |
| ISBN (elektronisch) | 9781510659612 |
| Publikationsstatus | Veröffentlicht - 8 März 2023 |
| Veranstaltung | SPIE Photonics West 2023 - Moscone Center, San Francisco, USA / Vereinigte Staaten Dauer: 28 Jan. 2023 → 2 Feb. 2023 https://spie.org/conferences-and-exhibitions/photonics-west |
Publikationsreihe
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Band | 12428 |
| ISSN (Print) | 0277-786X |
| ISSN (elektronisch) | 1996-756X |
Abstract
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.
ASJC Scopus Sachgebiete
- Werkstoffwissenschaften (insg.)
- Elektronische, optische und magnetische Materialien
- Physik und Astronomie (insg.)
- Physik der kondensierten Materie
- Mathematik (insg.)
- Angewandte Mathematik
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Informatik (insg.)
- Angewandte Informatik
Zitieren
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- BibTex
- RIS
Photonic Instrumentation Engineering X. Hrsg. / Lynda E. Busse; Yakov Soskind. SPIE, 2023. 124280R (Proceedings of SPIE - The International Society for Optical Engineering; Band 12428).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Characterization and digital aberration correction of a hyperspectral imaging system for plant disease detection
AU - Zabic, Miroslav
AU - Jose, Lijin
AU - Landes, Timm
AU - Fritz, Jan-Michael
AU - Weisheit, Inga
AU - Heinemann, Dag
PY - 2023/3/8
Y1 - 2023/3/8
N2 - 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.
AB - 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.
KW - hyperspectral imaging
KW - spatial resolution
KW - deconvolution
KW - plant disease detection
KW - agriculture
UR - http://www.scopus.com/inward/record.url?scp=85159777074&partnerID=8YFLogxK
U2 - 10.1117/12.2647833
DO - 10.1117/12.2647833
M3 - Conference contribution
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Photonic Instrumentation Engineering X
A2 - Busse, Lynda E.
A2 - Soskind, Yakov
PB - SPIE
T2 - SPIE Photonics West 2023
Y2 - 28 January 2023 through 2 February 2023
ER -