基于对象级的ADS40遥感影像分类研究

Object-Oriented Approach for ADS40 Image Classification

  • 摘要: 针对ADS40影像的空间分辨率高而光谱分辨率相对不足的特点,提出了一种基于多尺度分割的对象级遥感分类方法。首先通过多尺度分割获得影像对象,然后利用对象所包含的光谱特征、几何特征、拓扑特征来确定地物识别中可能要用到的各种特征参数,并建立对象间的分类层次结构图,最后利用模糊分类器逐级分层分类来提取地物信息。研究结果表明,面向对象的分类方法与传统方法相比,可显著提高分类精度,有效抑制“椒盐现象”的产生,更加适合于几何信息和结构信息丰富的ADS40影像的自动识别分类。通过对太原市ADS40影像进行分类验证了此方法的有效性。

     

    Abstract: ADS40 images with high spatial resolution have many more spatial characteristics than low-resolution image except spectral characteristics.We introduced a object-oriented classification method based on multi-scale segmentation to classify ADS40 image of Taiyuan City.Firstly,the whole image is multi-scale segmented to get objects.Then,The features of objects,such as spectral,geometrical and topological characteristics,were measured.The hierarchical structure for classification was built.Finally,we applied a fuzzy rule classifier to extract the classification information of ADS40 images.The research shows that the object-oriented method can improve the overall classification accuracy of ADS40 images,reduce the Pepper and Salt' Pheomenon effectively,and meet the requirement of ADS40 images classification compared with classical classification approaches.

     

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