A Novel Remote Sensing Image Change Detection Algorithm based on Game Theory Analysis and Hierarchical Fuzzy Clustering

DOI

10.2991/icmmct-16.2016.157How to use a DOI?

Keywords

Remote Sensing, Chang Detection, Game Theory, Fuzzy Clustering, Algorithm.

Abstract

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.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - 10.2991/icmmct-16.2016.157
ID  - Zhang2016/03
ER  -