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

机译:一种基于博弈论分析和分层模糊聚类的新型遥感图像改变检测算法

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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.
机译:本文提出了一种基于游戏理论分析和层级模糊聚类的新型遥感图像改变检测算法。该技术集成了纳什博弈论框架和层次结构化聚类方法。分析了图像恢复和分割的特征,用作具有最佳战术平衡的预处理步骤。随着层次结构的深度,密封程度内的分布式集群变少,在相同的处理水平,符合子歧管合并的当前层中的关闭条件,因此,我们选择分层模糊聚类以完成更改检测任务。实验结果证实了所提出的方法的有效性和可行性。与其他方法相比,它增加了变化检测过程的整体准确性和稳健性。

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