Limitations of subspace LDA in hyperspectral target recognition applications

@article{Prasad2007LimitationsOS,
  title={Limitations of subspace LDA in hyperspectral target recognition applications},
  author={Saurabh Prasad and Lori M. Bruce},
  journal={2007 IEEE International Geoscience and Remote Sensing Symposium},
  year={2007},
  pages={4049-4052}
}
Principal components analysis (PCA) is commonly used as a tool for feature space dimensionality reduction for various automatic target recognition (ATR) systems. Recently, PCA has also been employed in conjunction with linear discriminant analysis (LDA) to recondition ill posed LDA formulations. The key idea behind this approach is to use a PCA transformation to discard the null space of rank deficient scatter matrices so that LDA can be applied on this reconditioned space. This approach… CONTINUE READING