Low-Rank and Sparse Matrix Decomposition With Orthogonal Subspace Projection-Based Background Suppression for Hyperspectral Anomaly Detection.
Yixin YangJianqi ZhangShangzhen SongChi ZhangDelian LiuPublished in: IEEE Geosci. Remote. Sens. Lett. (2020)
Keyphrases
- anomaly detection
- hyperspectral
- low rank
- low rank matrix
- remote sensing
- image data
- high dimensional data
- low dimensional
- unsupervised learning
- convex optimization
- matrix factorization
- high dimensional
- subspace learning
- data sets
- singular value decomposition
- feature space
- nonnegative matrix factorization
- text classification
- principal component analysis
- microarray
- dimension reduction
- feature extraction
- image sequences