Automatic Classification of Remote Sensing Images Using Multiple Classifier Systems
المؤلفون المشاركون
Yang, Bin
Cao, Chunxiang
Li, Xiaowen
Xing, Ying
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-10-07
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1075172
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر