
Proceedings Paper
Multi-sensor decision level image fusion based on fuzzy theory and unsupervised FCMFormat | Member Price | Non-Member Price |
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Paper Abstract
We present a multi-sensor decision level image fusion algorithm based on fuzzy theory. The main interest of this method is its high speed classification and efficient fusion of complementary information. FCM classifiers are used for classification of each sensor image, and the classification results are fused by our fusion rule. The originality of this work is to define the fusion rule for multi-sensor image classification. Applications to SAR, infrared and multi-spectral image fusion produce interesting results.
Paper Details
Date Published: 9 June 2006
PDF: 7 pages
Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000J (9 June 2006); doi: 10.1117/12.681719
Published in SPIE Proceedings Vol. 6200:
Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China
Qingxi Tong; Wei Gao; Huadong Guo, Editor(s)
PDF: 7 pages
Proc. SPIE 6200, Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China, 62000J (9 June 2006); doi: 10.1117/12.681719
Show Author Affiliations
Yi Wang, Beihang Univ. (China)
Wei Chen, Beihang Univ. (China)
Wei Chen, Beihang Univ. (China)
Shiyi Mao, Beihang Univ. (China)
Published in SPIE Proceedings Vol. 6200:
Remote Sensing of the Environment: 15th National Symposium on Remote Sensing of China
Qingxi Tong; Wei Gao; Huadong Guo, Editor(s)
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