Sparse representation with multi-manifold analysis for texture classification from few training images ?
The prime pyramid expands the training dataset with less redundancy. Sparse representation provides a compact model for textural images in each class. Multi-manifold analysis improves discriminative power while mitigates overfitting. Reasonably high classification accuracy is achieved with very few training images.
sparse representation multi-manifold analysis texture classification few training image manifold learning