Classification of color remote sensing images based on multi-feature combination

XIONG Yu; ZUO Xiaoqing; HUANG Liang; CHEN Zhenting

doi:10.7510/jgjs.issn.1001-3806.2014.02.005

In order to improve the classification results and solve the universality in color sensing image classification using unique feature, a new support vector machine (SVM) color remote sensing image classification algorithm based on color feature and texture feature combination was proposed. The method used the combination of the color information and the texture information of color remote sensing image as the eigenvectors of SVM algorithm. The results show that the method can achieve higher precision compared with the traditional method using unique feature or texture feature. The method is effective to classify the remote sensing image.

Classification of color remote sensing images based on multi-feature combination

Corresponding author: ZUO Xiaoqing, zuoxq@163.com;

1. Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650500, China;

2. Faculty of Computer Information, Kunming Metallurgy College, Kunming 650033, China

Received Date: 2013-07-04

Accepted Date: 2013-07-17

Available Online: 2014-02-25

Abstract: In order to improve the classification results and solve the universality in color sensing image classification using unique feature, a new support vector machine (SVM) color remote sensing image classification algorithm based on color feature and texture feature combination was proposed. The method used the combination of the color information and the texture information of color remote sensing image as the eigenvectors of SVM algorithm. The results show that the method can achieve higher precision compared with the traditional method using unique feature or texture feature. The method is effective to classify the remote sensing image.

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Reference (16)

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Classification of color remote sensing images based on multi-feature combination

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通讯作者: 陈斌, bchen63@163.com

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