Globally maximizing, locally minimizing: Regularized Nonnegative Matrix Factorization for hyperspectral data feature extraction.
Mingyi HeFeng WeiXiuping JiaPublished in: WHISPERS (2012)
Keyphrases
- nonnegative matrix factorization
- hyperspectral data
- feature extraction
- principal component analysis
- least squares
- hyperspectral
- random projections
- hyperspectral images
- hyperspectral imagery
- principal components
- matrix factorization
- negative matrix factorization
- multispectral
- data representation
- remote sensing
- dimension reduction
- dimensionality reduction
- objective function
- infrared
- original data
- principle component analysis
- feature selection
- image processing
- face recognition
- feature vectors
- image classification
- target detection
- spectral clustering
- singular value decomposition
- image data
- high dimensional
- feature space
- linear discriminant analysis
- feature set
- k means
- image analysis
- document clustering
- training set
- data sets
- low dimensional