L0-Motivated Low Rank Sparse Subspace Clustering for Hyperspectral Imagery.
Long TianQian DuIvica KoprivaPublished in: IGARSS (2020)
Keyphrases
- low rank
- subspace clustering
- hyperspectral imagery
- high dimensional data
- low rank matrix
- rank minimization
- subspace projection
- high dimensional
- sparse representation
- affinity matrix
- subspace clusters
- multispectral
- hyperspectral images
- low dimensional
- hyperspectral
- remote sensing
- nearest neighbor
- high dimensionality
- spatial resolution
- data sets
- dimensionality reduction
- target detection
- original data
- kernel matrix
- high dimensional feature space
- data analysis
- data points
- missing data
- clustering algorithm
- singular value decomposition
- convex optimization
- infrared
- lower dimensional
- sparse coding
- matrix factorization
- linear combination
- semi supervised
- input space
- high order
- multi band
- image data
- sparse matrix
- clustering method
- principal component analysis
- object recognition
- computer vision
- machine learning