Efficient Noise Filtration of Images by Low-Rank Singular Vector Approximations of Geodesics' Gramian Matrix.
Kelum GajamannageYonggi ParkSunil MathurPublished in: CoRR (2022)
Keyphrases
- low rank
- missing data
- low rank matrix
- eigendecomposition
- singular values
- matrix decomposition
- singular value decomposition
- image data
- linear combination
- convex optimization
- rank minimization
- matrix factorization
- matrix completion
- input image
- high dimensional data
- semi supervised
- trace norm
- kernel matrix
- image classification
- gaussian noise
- high order
- low rank matrices
- sparse matrix
- nuclear norm
- geometric structure
- binary matrix
- small number
- input data
- factorization methods
- data sets
- low rank and sparse
- low rank approximation
- covariance matrix
- principal component analysis
- computer vision