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由于K-means 聚类方法对遥感图像进行分类时，对训练样本的选取依赖性很大，容易陷入局部最优的陷阱的情况，本文提出利用模拟退化算法对K-means 的聚类进行优化以获得 全局最优解的分类新方案。并以多波段影像为例进行验证分析，结果表明该方法可行，收敛 结果优于K-means 聚类算法，分类精度相对传统的K-means 算法更高。-Because K-means clustering classification depend on the training sample selecti