DIMENSIONALITY REDUCTION

Fully Group Convolutional Neural Networks for Robust Spectral-Spatial Feature Learning

Convolutional neural network (CNN) has been widely applied in hyperspectral image (HSI) classification exhibiting excellent performance. Weak generalization of CNN models to different datasets is a common issue in this domain largely because of …

Semisupervised local discriminant analysis for feature extraction in hyperspectral images

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 …

Classification of hyperspectral data over urban areas using directional morphological profiles and semi-supervised feature extraction

When using morphological features for the classification of high resolution hyperspectral images from urban areas, one should consider two important issues. The first one is that classical morphological openings and closings degrade the object …