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

Miroslav Zabic; Lijin Jose; Timm Landes; Jan-Michael Fritz; Inga Weisheit; Dag Heinemann

doi:10.1117/12.2647833

8 March 2023 Characterization and digital aberration correction of a hyperspectral imaging system for plant disease detection

Miroslav Zabic, Lijin Jose, Timm Landes, Jan-Michael Fritz, Inga Weisheit, Dag Heinemann

Author Affiliations +

Proceedings Volume 12428, Photonic Instrumentation Engineering X; 124280R (2023) https://doi.org/10.1117/12.2647833
Event: SPIE OPTO, 2023, San Francisco, California, United States

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.

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Citation Download Citation

Miroslav Zabic, Lijin Jose, Timm Landes, Jan-Michael Fritz, Inga Weisheit, and Dag Heinemann "Characterization and digital aberration correction of a hyperspectral imaging system for plant disease detection", Proc. SPIE 12428, Photonic Instrumentation Engineering X, 124280R (8 March 2023); https://doi.org/10.1117/12.2647833

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