A morphological approach for feature space partitioning

Barata T.; Pina P.

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A morphological approach for feature space partitioning

机译：特征空间分割的一种形态学方法

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A mathematical morphology-based methodology to construct decision region borders that geometrically model the training sets of points is presented in this letter. It is shown that the incorporation of the geometric features of the training sets leads to higher classification rates. Our approach is illustrated with two features of seven land-cover classes [forest (3), soil (2), vegetation, and water] constructed from remotely sensed images of a region in the center of Portugal.

机译：在这封信中介绍了一种基于数学形态学的方法来构建决策区域边界，以几何方式对点的训练集进行建模。结果表明，训练集的几何特征的合并导致更高的分类率。我们的方法通过葡萄牙中部地区的遥感图像构建的七个土地覆盖类别（森林（3），土壤（2），植被和水）的两个特征得到说明。

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《IEEE Geoscience and Remote Sensing Letters》 |2006年第1期|p.173-177|共5页
作者
Barata T.; Pina P.;
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正文语种 eng
中图分类测绘遥感技术;
关键词
feature extraction; geophysical signal processing; geophysical techniques; image texture; remote sensing; Portugal; anisotropic distance function; classification rates; decision region borders; directional structuring elements; feature space partitioning; forestry;

机译：特征提取;地球物理信号处理;地球物理技术;图像纹理;遥感;葡萄牙;各向异性距离函数;分类率;决定区域边界;方向性结构元素;特征空间划分;林业;

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A morphological approach for feature space partitioning

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