Mahalanobis distance-based kernel supervised machine learning in spectral dimensionality reduction for hyperspectral imaging remote sensing.
Jing LiuYulong QiaoPublished in: Int. J. Distributed Sens. Networks (2020)
Keyphrases
- hyperspectral imaging
- supervised machine learning
- remote sensing
- dimensionality reduction
- hyperspectral
- hyperspectral imagery
- kernel pca
- hyperspectral images
- feature space
- hyperspectral data
- multispectral
- target detection
- change detection
- hyperspectral remote sensing
- remote sensing images
- spectral resolution
- high resolution
- high dimensional
- band selection
- multi spectral images
- image processing
- high dimensional data
- pattern recognition
- kernel function
- image analysis
- image fusion
- principal component analysis
- active learning
- low dimensional
- feature extraction
- multispectral images
- supervised learning
- satellite images
- unsupervised learning
- random projections
- feature selection
- spectral bands
- data points
- kernel methods
- machine learning
- high dimensional feature space
- dimension reduction
- training data
- multi band
- reinforcement learning
- infrared
- learning algorithm
- semi supervised