H.6.3.3. Pattern analysis
Overlap-based feature weighting: The feature extraction of Hyperspectral remote sensing imagery

M. Imani; H. Ghassemian

Volume 3, Issue 2 , July 2015, , Pages 181-190

http://dx.doi.org/10.5829/idosi.JAIDM.2015.03.02.07

Abstract
  Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very ...  Read More

H.6.3.2. Feature evaluation and selection
Feature reduction of hyperspectral images: Discriminant analysis and the first principal component

Maryam Imani; Hassan Ghassemian

Volume 3, Issue 1 , March 2015, , Pages 1-9

http://dx.doi.org/10.5829/idosi.JAIDM.2015.03.01.01

Abstract
  When the number of training samples is limited, feature reduction plays an important role in classification of hyperspectral images. In this paper, we propose a supervised feature extraction method based on discriminant analysis (DA) which uses the first principal component (PC1) to weight the scatter ...  Read More