New Robust PCA for Outliers and Heavy Sparse Noises' Detection via Affine Transformation, the L ∗ , w and L 2, 1 Norms, and Spatial Weight Matrix in High-Dimensional Images: From the Perspective of Signal Processing.
Peidong LiangHabte Tadesse LikassaChentao ZhangJielong GuoPublished in: Int. J. Math. Math. Sci. (2021)
Keyphrases
- high dimensional
- affine transformation
- geometric transformations
- transformed images
- signal processing
- feature points
- image registration
- weight matrix
- image matching
- partial occlusion
- affine invariant
- image set
- dimensionality reduction
- low dimensional
- input image
- feature space
- data points
- image analysis
- three dimensional
- principal component analysis
- image classification
- keypoints
- similarity search
- image processing
- object recognition
- edge detection
- image features
- image retrieval
- similarity measure
- feature extraction
- computer vision
- segmentation algorithm
- face images
- test images
- pattern recognition
- reinforcement learning
- face recognition