H.6.5.10. Remote sensing
1. Nonparametric Spectral-Spatial Anomaly Detection

M. Imani

Volume 8, Issue 1 , Winter 2020, , Pages 95-103

Abstract
  Due to abundant spectral information contained in the hyperspectral images, they are suitable data for anomalous targets detection. The use of spatial features in addition to spectral ones can improve the anomaly detection performance. An anomaly detector, called nonparametric spectral-spatial detector ...  Read More

H.6.3.2. Feature evaluation and selection
2. 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