@inproceedings{5f1f3a886db74cd6a1508a2173920b75,
title = "Locality-preserving discriminant analysis for hyperspectral image classification using local spatial information",
abstract = "Locality-preserving projection as well as local Fisher discriminant analysis is applied for dimensionality reduction of hyperspectral imagery based on both spatial and spectral information. These techniques preserve the local geometric structure of hyperspectral data into a low-dimensional subspace wherein a Gaussian-mixture-model classifier is then considered. In the proposed classification system, local spatial information - which is expected to be more multimodal than strictly spectral features - is used. Results with experimental hyperspectral data demonstrate that this system outperforms traditional classification approaches.",
keywords = "Dimensionality reduction, hyperspectral data, linear discriminant analysis, pattern classification",
author = "Wei Li and Saurabh Prasad and Zhen Ye and Fowler, \{James E.\} and Minshan Cui",
year = "2012",
doi = "10.1109/IGARSS.2012.6351702",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4134--4137",
booktitle = "IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium",
address = "United States",
note = "32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 ; Conference date: 22-07-2012 Through 27-07-2012",
}