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Multi-feature model analysis-based target identification for remote sensing image

机译:基于多特征模型分析的遥感图像目标识别

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Recently, target identification has become a key topic due to the richness of nature resources contained in high-resolution remote sensing image. Many algorithms have been proposed in this aspect. In order to reduce algorithmic complexity and shorten computing cost, a multi-feature analysis model is proposed to identify targets in remote sensing images. The originality of the method includes two aspects. (1) City planning diagram, which is a vector file in the term of polygons of indispensable attributes, is used for image partition. (2) Multiple features are modeled, and then an identification rule is developed based on the model and minimum distance classification. Experimental results show that the proposed method is reliable in performing target identification.
机译:最近,由于高分辨率遥感图像中包含的自然资源丰富,目标识别已成为一个关键话题。 在这方面提出了许多算法。 为了降低算法复杂性和缩短计算成本,提出了一种多特征分析模型来识别遥感图像中的目标。 该方法的原创性包括两个方面。 (1)城市规划图,它是不可缺少属性的多边形中的一个矢量文件,用于图像分区。 (2)建模多个特征,然后基于模型和最小距离分类开发识别规则。 实验结果表明,该方法在执行目标识别方面是可靠的。

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