Semisupervised Local Discriminant Analysis for Feature Extraction in Hyperspectral Images

@article{Liao2013SemisupervisedLD,
  title={Semisupervised Local Discriminant Analysis for Feature Extraction in Hyperspectral Images},
  author={Wenzi Liao and Aleksandra Pizurica and Paul Scheunders and Wilfried Philips and Youguo Pi},
  journal={IEEE Transactions on Geoscience and Remote Sensing},
  year={2013},
  volume={51},
  pages={184-198}
}
We propose a novel semisupervised local discriminant analysis method for feature extraction in hyperspectral remote sensing imagery, with improved performance in both ill-posed and poor-posed conditions. The proposed method combines unsupervised methods (local linear feature extraction methods and supervised method (linear discriminant analysis) in a novel framework without any free parameters. The underlying idea is to design an optimal projection matrix, which preserves the local neighborhood… CONTINUE READING
Highly Cited
This paper has 77 citations. REVIEW CITATIONS

14 Figures & Tables

Topics

Statistics

01020201320142015201620172018
Citations per Year

78 Citations

Semantic Scholar estimates that this publication has 78 citations based on the available data.

See our FAQ for additional information.