A comparison of principal components and endmember-based contextual learning for hyperspectral anomaly classification.
Christopher R. RattoKenneth D. MortonLeslie M. CollinsPeter A. TorrionePublished in: WHISPERS (2011)
Keyphrases
- hyperspectral images
- hyperspectral data
- hyperspectral
- principal components
- hyperspectral imagery
- spectral data
- multispectral
- hyperspectral image classification
- principal component analysis
- pixel classification
- pattern recognition
- unsupervised learning
- infrared
- mutual information
- data sets
- machine learning
- feature set
- active learning
- feature extraction
- decision trees
- image processing
- feature selection
- learning algorithm