Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems
Joint Authors
Yang, Bin
Cao, Chunxiang
Li, Xiaowen
Xing, Ying
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
It is a challenge to obtain accurate result in remote sensing images classification, which is affected by many factors.
In this paper, aiming at correctly identifying land use types reflec ted in remote sensing images, support vector machine, maximum likelihood classifier, backpropagation neural network, fuzzy c-means, and minimum distance classifier were combined to construct three multiple classifier systems (MCSs).
Two MCSs were implemented, namely, comparative major voting (CMV) and Bayesian average (BA).
One method called WA-AHP was proposed, which introduced analytic hierarchy process into MCS.
Classification results of base classifiers and MCSs were compared with the ground truth map.
Accuracy indicators were computed and receiver operating characteristic curves were illustrated, so as to evaluate the performance of MCSs.
Experimental results show that employing MCSs can increase classification accuracy significantly, compared with base classifiers.
From the accuracy evaluation result and visual check, the best MCS is WA-AHP with overall accuracy of 94.2%, which overmatches BA and rivals CMV in this paper.
The producer’s accuracy of each land use type proves the good performance of WA-AHP.
Therefore, we can draw the conclusion that MCS is superior to base classifiers in remote sensing image classification, and WA-AHP is an efficient MCS.
American Psychological Association (APA)
Yang, Bin& Cao, Chunxiang& Xing, Ying& Li, Xiaowen. 2015. Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1075172
Modern Language Association (MLA)
Yang, Bin…[et al.]. Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1075172
American Medical Association (AMA)
Yang, Bin& Cao, Chunxiang& Xing, Ying& Li, Xiaowen. Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1075172
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075172