神经网络敏感性分析的高光谱遥感影像降维与分类方法

doi:10.11999/JEIT160052

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Abstract

The high dimensions of hyperspectral remote sensing images will cause the redundancy of information and complexity of data processing, which also brings tremendous computing workload and damages application accuracy. Therefore, before the analysis of hyperspectral image processing, it is necessary to reduce the high dimensions of hyperspectral data. The Sensitivity Analysis (SA) of artificial neural network can be used in dimension reduction of the model. Now the Sensitivity Analysis of artificial neural network is applied to dimension reduction for hyperspectral remote sensing images in the paper. First of all, all bands are divided into several groups as long as a lower correlation exists between adjacent bands. Furthermore, Differential Evolution (DE) algorithm is used for optimizing neural network structure. Moreover, the bands which make small contribution will be given up based on Ruck sensitivity analysis method. Finally, experiments are conducted with AVIRIS images. The results show that the proposed method can get high classification accuracy of 85.83% at small training samples, 0.31% higher than the best one among other similar methods of dimension reduction and classification.

Key words： Dimension reduction for hyperspectral remote sensing images Sensitivity Analysis (SA) of artificial neural network Subspace decomposition Differential Evolution (DE) Ruck Sensitivity Analysis (SA)

Received: 13 January 2016 Published: 01 September 2016

PACS:

TP391

Fund:

The Fundamental Research Funds for the Central Universities (2014B13214, 2015B26914), The Projects in the National Science & Technology Pillar Program during the Twelfth Five-year Plan Period (2015BAB07B03), The National Undergraduate Training Program for Innovation and Entrepreneurship of Hohai University (201610294061)

Corresponding Authors: LI Chenming E-mail: lichenming55@163.com

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	GAO Hongmin
	LI Chenming
	ZHOU Hui
	ZHANG Zhen
	CHEN Linghui
	HE Zhenyu

Cite this article:

GAO Hongmin,LI Chenming,ZHOU Hui等. Dimension Reduction and Classification of Hyperspectral Remote Sensing Images Based on Sensitivity Analysis of Artificial Neural Network[J]. JEIT, 2016, 38(11): 2715-2723.

URL:

http://jeit.ie.ac.cn/EN/10.11999/JEIT160052 OR http://jeit.ie.ac.cn/EN/Y2016/V38/I11/2715

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