Hierarchical Sparse Subspace Clustering (HESSC): An Automatic Approach for Hyperspectral Image Analysis.
Kasra Rafiezadeh ShahiMahdi KhodadadzadehLaura TusaPedram GhamisiRaimon Tolosana-DelgadoRichard GloaguenPublished in: Remote. Sens. (2020)
Keyphrases
- hyperspectral
- subspace clustering
- remote sensing
- image analysis
- multispectral
- subspace projection
- high dimensional
- hyperspectral images
- hyperspectral imagery
- subspace clusters
- high dimensional data
- clustering method
- hyperspectral data
- infrared
- spatial resolution
- spectral bands
- hyperspectral remote sensing
- hyperspectral imaging
- target detection
- change detection
- image data
- computer vision
- image processing
- clustering algorithm
- satellite images
- discriminant analysis
- subspace projections
- pattern recognition
- image segmentation
- database
- face recognition
- high resolution
- sparse representation
- low dimensional
- information content
- multispectral images
- decision trees
- original data
- linear discriminant analysis
- spectral data
- machine learning
- neural network
- spectral resolution
- information extraction
- dimensionality reduction