Extended profiles with morphological attribute filters for the analysis of hyperspectral data
Extended profiles with morphological attribute filters for the analysis of hyperspectral data
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DOI：
10.1080/01431161.2010.512425
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发表时间：
2010-01-01
影响因子：
3.4
通讯作者：
Bruzzone, Lorenzo
中科院分区：
文献类型：
--
作者：
Dalla Mura, Mauro;Benediktsson, Jon Atli;Bruzzone, Lorenzo
提出了扩展属性配置文件和扩展多属性配置文件，用于高光谱高分辨率图像的分析。这些扩展轮廓基于形态属性过滤器，并且通过多级分析，能够提取空间特征，相对于传统的扩展形态轮廓，可以更好地对空间信息进行建模。由所提出的扩展配置文件提取的特征被考虑用于分类任务。分析中考虑了为意大利帕维亚市获取的两个高光谱高分辨率数据集。所引入的算子在空间信息建模中的有效性得到了相对于传统扩展形态轮廓所获得的更高分类精度的证明。
Extended attribute profiles and extended multi-attribute profiles are presented for the analysis of hyperspectral high-resolution images. These extended profiles are based on morphological attribute filters and, through a multi-level analysis, are capable of extracting spatial features that can better model the spatial information, with respect to conventional extended morphological profiles. The features extracted by the proposed extended profiles were considered for a classification task. Two hyperspectral high-resolution datasets acquired for the city of Pavia, Italy, were considered in the analysis. The effectiveness of the introduced operators in modelling the spatial information was proved by the higher classification accuracies obtained with respect to those achieved by a conventional extended morphological profile.