@inproceedings{37972e872bf44a8fb6ec03f9e4af02b9,
title = "Improved classification of conservation tillage practices using hyperspectral imagery with spatial-spectral features",
abstract = "Classification of conservation tillage practices from hyper-spectral imagery is challenging due to spectral similarity between soils and senescent crop residues. In this paper, a novel classifier using both spectral and spatial information is proposed for hyperspectral image classification. Three steps are included: (1) a feature extraction method using a very simple local averaging filter to produce the joint spectral-spatial features; (2) an efficient local Fisher discriminant analysis projection for dimensionality reduction and class separability enhancement; and (3) the typical k-nearest neighbor classifier for final classification. Experimental results using real hy-perspectral data demonstrate the benefits of the proposed approach, which can outperform other popular classifiers, such as support vector machine with composite kernel.",
keywords = "Conservation tillage, feature extraction, hyperspectral data, pattern classification",
author = "Wei Li and Qiong Ran and Qian Du and Chenghai Yang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014 ; Conference date: 11-08-2014 Through 14-08-2014",
year = "2014",
month = sep,
day = "25",
doi = "10.1109/Agro-Geoinformatics.2014.6910589",
language = "English",
series = "2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2014 The 3rd International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2014",
address = "United States",
}