H.6.3.2. Feature evaluation and selection
1. Feature extraction of hyperspectral images using boundary semi-labeled samples and hybrid criterion

M. Imani; H. Ghassemian

Volume 5, Issue 1 , Winter 2017, , Pages 39-53

Abstract
  Feature extraction is a very important preprocessing step for classification of hyperspectral images. The linear discriminant analysis (LDA) method fails to work in small sample size situations. Moreover, LDA has poor efficiency for non-Gaussian data. LDA is optimized by a global criterion. Thus, it ...  Read More