Abundance-Indicated Subspace for Hyperspectral Classification With Limited Training Samples.
Shuyuan XuJun LiMahdi KhodadadzadehAndrea MarinoniPaolo GambaBo LiPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2019)
Keyphrases
- training samples
- hyperspectral
- feature space
- test sample
- hyperspectral images
- training set
- high dimensional
- nearest neighbor classifier
- hyperspectral data
- learning algorithm
- hyperplane
- remote sensing
- training data
- pixel classification
- supervised learning
- hyperspectral imagery
- hyperspectral image classification
- multispectral
- infrared
- image data
- hyperspectral remote sensing
- representative samples
- target detection
- change detection
- classification accuracy
- spatial resolution
- machine learning
- decision trees
- image segmentation
- feature extraction
- pattern recognition
- feature vectors
- base classifiers
- principal component analysis
- dimension reduction
- high dimensionality
- face images
- dimensionality reduction
- support vectors
- kernel function
- information content
- low dimensional
- high dimensional data