• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Change Detection in Bitemporal Remote Sensing Images by using Feature Fusion and Fuzzy C-Means

Vol. 12, No.4, April 30, 2018
10.3837/tiis.2018.04.017, Download Paper (Free):

Abstract

Change detection of remote sensing images is a profound challenge in the field of remote sensing image analysis. This paper proposes a novel change detection method for bitemporal remote sensing images based on feature fusion and fuzzy c-means (FCM). Different from the state-of-the-art methods that mainly utilize a single image feature for difference image construction, the proposed method investigates the fusion of multiple image features for the task. The subsequent problem is regarded as the difference image classification problem, where a modified fuzzy c-means approach is proposed to analyze the difference image. The proposed method has been validated on real bitemporal remote sensing data sets. Experimental results confirmed the effectiveness of the proposed method.


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Cite this article

[IEEE Style]
Xin Wang, Jing Huang, Yanli Chu, Aiye Shi and Lizhong Xu, "Change Detection in Bitemporal Remote Sensing Images by using Feature Fusion and Fuzzy C-Means," KSII Transactions on Internet and Information Systems, vol. 12, no. 4, pp. 1714-1729, 2018. DOI: 10.3837/tiis.2018.04.017

[ACM Style]
Wang, X., Huang, J., Chu, Y., Shi, A., and Xu, L. 2018. Change Detection in Bitemporal Remote Sensing Images by using Feature Fusion and Fuzzy C-Means. KSII Transactions on Internet and Information Systems, 12, 4, (2018), 1714-1729. DOI: 10.3837/tiis.2018.04.017