Multi-Sensor Spectral Imaging of Geological Samples: A Data Fusion Approach Using Spatio-Spectral Feature Extraction

Multi-Sensor Spectral Imaging of Geological Samples: A Data Fusion Approach Using Spatio-Spectral Feature Extraction

Rapid, efficient and reproducible drillcore logging is fundamental in mineral exploration. Drillcore mapping has evolved rapidly in the recent decade, especially with the advances in hyperspectral spectral imaging. A wide range of imaging sensors is now available, providing rapidly increasing spectr...

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Bibliographic Details
Main Authors: Sandra Lorenz, Peter Seidel, Pedram Ghamisi, Robert Zimmermann, Laura Tusa, Mahdi Khodadadzadeh, I. Cecilia Contreras, Richard Gloaguen
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Sensors
Subjects:
hyperspectral
spectral imaging
multi-sensor data
data fusion
feature extraction
support vector machine (SVM)
orthogonal total variation component analysis (OTVCA)
mineral exploration
Online Access:https://www.mdpi.com/1424-8220/19/12/2787

Internet

https://www.mdpi.com/1424-8220/19/12/2787

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