S. Paulus, F. Ispizua, et al.: Using hyperspectral cameras in greenhouses – introduction into data processing and application scenarios

Facundo Ramón Ispizua Yamati is a Doctoral Student at the Institute of Sugar Beet Research in Göttingen. His research interests are 3D and hyperspectral imaging of plants in greenhouse and field, sensor fusion, and machine learning.

Hyperspectral Imaging has become a valid tool for plant phenotyping and, thus, for imaging plants in greenhouses. Nevertheless, hyperspectral imaging is affected by various components as there are camera calibration, the light condition, the data pre-processing, and the way the data is prepared for machine learning algorithms. In this work, the authors show the main application field for using hyperspectral imaging of plants as well as a general workflow describing how hyperspectral data should be processed. The latter helps to establish a high degree of comparability for plant images of different sensor setups.

Authors: Stefan Paulus, Anne-Katrin Mahlein, Facundo Ispizua Yamati & Abel Barreto