ITM Web Conf.
Volume 7, 20163rd Annual International Conference on Information Technology and Applications (ITA 2016)
|Number of page(s)||3|
|Section||Session 2: Signal and Image Processing|
|Published online||21 November 2016|
A Hyper spectral Images Classification Method Based on Maximum Scatter Discriminant Analysis
1 College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, 730070, China
2 College of Computer Science & Engineering, Northwest Normal University, Lanzhou, 730070, China
To overcome “small sample size problem” problem faced by some hyper spectral classification methods, the Maximum Scatter Discriminant criterion is used to analyzed hyperspectral data. Maximum Scatter Discriminant analysis searches for the project axes by maximizing the difference of between-class scatter and within-class scatter matrices, which avoid to calculate the inverse of matrices. Experiment results on Indian Pines HSI data set show that the proposed method outperforms the other methods in terms of recognition accuracy. The proposed method is an effective and feasible method for hyper pectral data classification.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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