A novel hyperspectral classification method based on C5.0 decision tree of multiple combined classifiers

Meng Wang*, Kun Gao, Li Jing Wang, Xiang Hu Miu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

18 Citations (Scopus)

Abstract

It is difficult for a single classifier to resolve the problem of high dimension in the hyperspectral image classification applications. Combination of multiple classifiers can make full use of the complementary of the existing classifiers, thus owns better classification performance. A novel multiple classifiers based on C5.0 decision tree is proposed. It reduces the hyperspectral dimension through wavelet-PCA transform algorithm firstly. Then three supervised classifiers, namely Minimum Distance, Maximum Likelihood and SVM, combined by C5.0 decision tree, are used to realize hyperspectral classification. Experiments based on AVIRIS hyperspectral image data show that higher classification accuracy may be achieved via the multiple combined classifiers than a single sub-classifier. The proposed method can reduce the dimension of features and improve the classification performance efficiently.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Computational and Information Sciences, ICCIS 2012
Pages373-376
Number of pages4
DOIs
Publication statusPublished - 2012
Event4th International Conference on Computational and Information Sciences, ICCIS 2012 - Chongqing, China
Duration: 17 Aug 201219 Aug 2012

Publication series

NameProceedings - 4th International Conference on Computational and Information Sciences, ICCIS 2012

Conference

Conference4th International Conference on Computational and Information Sciences, ICCIS 2012
Country/TerritoryChina
CityChongqing
Period17/08/1219/08/12

Keywords

  • C5.0 decision tree
  • classification accuracy
  • multiple classifiers

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Wang, M., Gao, K., Wang, L. J., & Miu, X. H. (2012). A novel hyperspectral classification method based on C5.0 decision tree of multiple combined classifiers. In Proceedings - 4th International Conference on Computational and Information Sciences, ICCIS 2012 (pp. 373-376). Article 6300514 (Proceedings - 4th International Conference on Computational and Information Sciences, ICCIS 2012). https://doi.org/10.1109/ICCIS.2012.33