Optimal Spectral Shrinkage and PCA With Heteroscedastic Noise.
William E. LeebElad RomanovPublished in: IEEE Trans. Inf. Theory (2021)
Keyphrases
- principal component analysis
- linear discriminant analysis
- denoising
- noise level
- dynamic programming
- face recognition
- principal components
- dimensionality reduction
- minimum mean square error
- gaussian noise
- noise reduction
- signal to noise ratio
- random noise
- image processing
- independent component analysis
- noisy data
- least squares
- feature vectors
- optimal solution
- feature extraction
- noise removal
- image noise
- spectral analysis