利用众数滤波对监督分类训练样本纯化的研究

Studies on the purification of training samples in supervised classification by mode filtering

  • 摘要: 分析了当遥感分类类别存在光谱特征重叠时,以训练区数据估计类别总体特征发生偏差的原因和性质,提出运用众数滤波(Majority滤波)对训练区进行纯化.一个例子的研究表明,尤其在提取某一类或少数几类专题信息时,如果不关心其余专题信息的提取精度,Majority滤波是一种较好训练区纯化方式.

     

    Abstract: This paper analyses the attribution and cause of the deviation of estimating the class population's feature by training samples.We perform a supervised classification on the remote sensing imagine and some classes have overlapping on their distribution curves,and propose using the technology of mode filtering (Majority filtering) to carry on the purification of the training area.One example shows,especially at the time of drawing some one or a few several kinds of thematic information.If the accuracy of ...

     

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