@inproceedings{1ca074d2c1644fe3a11ceba26be7de9a,
title = "Discriminative weighted band selection via one-class SVM for hyperspectral imagery",
abstract = "In the task of hyperspectral image classification, band selection is often adopted to select a subset of informative bands to reduce the computation and storage cost. We propose a supervised band selection method which allows calculation of a discriminative weight for each band. Specifically, we consider discriminative bands as those that contribute more positive scores to a one-class classifier than those for other classes during the training stage. Based on this observation, we learn discriminative a band weight vector for each class, then bands with larger discriminative weights can be selected. Our method can be efficiently solved in one-class SVM framework. Experimental results demonstrate the effectiveness of our method.",
keywords = "Band selection, hyperspectral imagery, image classification, one-class SVM, supervised learning",
author = "Yu Tang and Enlong Fan and Cheng Yan and Xiao Bai and Jun Zhou",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 ; Conference date: 10-07-2016 Through 15-07-2016",
year = "2016",
month = nov,
day = "1",
doi = "10.1109/IGARSS.2016.7729714",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2765--2768",
booktitle = "2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings",
address = "美国",
}