Constrained Low-Tubal-Rank Tensor Recovery for Hyperspectral Images Mixed Noise Removal by Bilateral Random Projections.
Hao ZhangXi-Le ZhaoTai-Xiang JiangMichael Kwok-Po NgPublished in: IGARSS (2019)
Keyphrases
- noise removal
- random projections
- hyperspectral data
- hyperspectral images
- dimensionality reduction
- image enhancement
- denoising
- anisotropic diffusion
- noise reduction
- hyperspectral
- hyperspectral imagery
- edge detection
- random sampling
- image reconstruction
- dimension reduction
- sparse representation
- original data
- principal component analysis
- low dimensional
- hash functions
- remote sensing
- image denoising
- high order
- pattern recognition
- image analysis
- multispectral images
- gaussian noise
- multispectral
- high dimensionality
- higher order
- feature selection
- machine learning
- feature extraction
- feature space
- high dimensional
- data points
- image data
- signal to noise ratio
- data sets