基于模糊核P系统的高光谱图像聚类算法研究

Shi Qiu, Geng Zhang, Miao Zhang
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引用次数: 0

摘要

针对光谱图像聚类的难点,提出了一种基于模糊核P系统的图像聚类算法。通过对模糊聚类和核聚类的分析,构建模糊核系统对组织P系统进行优化,并协调各单元在映射空间中计算最优聚类中心,实现并行计算。它可以降低初始聚类中心的灵敏度,提高算法的全局搜索能力,避免陷入局部最小值,提高算法的聚类性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Clustering Algorithm of Hyperspectral Images Based on Fuzzy Kernel P System
According to the difficulty of spectral image clustering, an image clustering algorithm is proposed based on fuzzy kernel P system. Through the analysis of fuzzy clustering and kernel clustering, the fuzzy kernel system is built to optimize the organizational P system, and all cells are coordinated to calculate the optimal clustering center in the mapping space to achieve parallel computing. It can reduce the sensitivity of the initial clustering center, improve the global search ability of the algorithm, avoid falling into the local minimum, and improve the clustering performance of the algorithm.
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