在常用的方法中，基于区域灰度平均的算法使图像模糊，而基于样条插值的算法计算耗时。

In the common methods, the algorithm based on the average of region gray makes image blur, and the algorithm based on spline interpolation wastes time.

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本文提出了一种基于知识的遥感图像模糊分类算法，在传统的模糊分类方法中加入了从GIS数据库中发现的知识，用它来辅助进行遥感图像分类。

In this paper, a knowledge-based fuzzy image classification method is proposed. In the method, knowledge discovery from GIS is introduced in to assist fuzzy image classification.

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最后采用几幅不同的图像进行实验，结果表明该方法可行有效，并且对于模糊图像，算法也能获得满意的结果。

Using some images in experiment, the results show this method is feasible and efficient, and fits for fuzzy images too.

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