A Novel Remote Sensing Image Change Detection Algorithm based on Game Theory Analysis and Hierarchical Fuzzy Clustering
Xinyu Zhang, Xuan Zhuang, Hang Ji
Available Online March 2016.
- https://doi.org/10.2991/icmmct-16.2016.157How to use a DOI?
- Remote Sensing, Chang Detection, Game Theory, Fuzzy Clustering, Algorithm.
- A novel remote sensing image change detection algorithm based on game theory analysis and hierarchical fuzzy clustering is proposed in this paper. This technique integrates the Nash game theory framework and the hierarchical structured clustering approach. Characteristics of the image restoration and segmentation are analyzed to serve as the pre-processing step with the optimal tactical balance. With the deepening of the hierarchy, distributed clusters inside tightness degree gets less, at the same level of processing conforms to close conditions in current layer with sub-manifold merge, therefore, we choose hierarchical fuzzy clustering to finalize the change detection task. Experimental result confirms the effectiveness and feasibility of the proposed methodology. It increases the overall accuracy and robustness of the change detection processes compared with other approaches.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xinyu Zhang AU - Xuan Zhuang AU - Hang Ji PY - 2016/03 DA - 2016/03 TI - A Novel Remote Sensing Image Change Detection Algorithm based on Game Theory Analysis and Hierarchical Fuzzy Clustering BT - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology PB - Atlantis Press SP - 805 EP - 809 SN - 2352-5401 UR - https://doi.org/10.2991/icmmct-16.2016.157 DO - https://doi.org/10.2991/icmmct-16.2016.157 ID - Zhang2016/03 ER -