Cargando…
Elimination of Leaf Angle Impacts on Plant Reflectance Spectra Using Fusion of Hyperspectral Images and 3D Point Clouds
During recent years, hyperspectral imaging technologies have been widely applied in agriculture to evaluate complex plant physiological traits such as leaf moisture content, nutrient level, and disease stress. A critical component of this technique is white referencing used to remove the effect of n...
Autores principales: | Zhang, Libo, Jin, Jian, Wang, Liangju, Rehman, Tanzeel U., Gee, Mark T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824419/ https://www.ncbi.nlm.nih.gov/pubmed/36616642 http://dx.doi.org/10.3390/s23010044 |
Ejemplares similares
-
Stress Distribution Analysis on Hyperspectral Corn Leaf Images for Improved Phenotyping Quality
por: Ma, Dongdong, et al.
Publicado: (2020) -
Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants
por: Wang, Liangju, et al.
Publicado: (2020) -
Implementation of the directly-georeferenced hyperspectral point cloud
por: Inamdar, Deep, et al.
Publicado: (2021) -
Improving High-Throughput Phenotyping Using Fusion of Close-Range Hyperspectral Camera and Low-Cost Depth Sensor
por: Huang, Peikui, et al.
Publicado: (2018) -
Leaf reflectance spectra capture the evolutionary history of seed plants
por: Meireles, José Eduardo, et al.
Publicado: (2020)