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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Band Selection for Hyperspectral Imagery: A New Approach Based on Complex Networks
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Band Selection for Hyperspectral Imagery: A New Approach Based on Complex Networks

机译：高光谱图像的波段选择：基于复杂网络的新方法

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摘要

In recent years, band selection is becoming a popular approach to reduce the dimensionality of hyperspectral data while preserving the desired information for target detection and classification analysis. This letter presents a new method for unsupervised band selection by transforming the hyperspectral data into complex networks. By analyzing the networks' topological feature corresponding to each band, one can easily evaluate the statistical characteristics and intrinsic properties of the signals. The proposed method searches for the network set which is most qualified for demarcating and identifying different substance signatures, and then, the network set's corresponding bands are regarded as the descried output results. This network measure is a new criterion for band selection. Experimental results demonstrate that the proposed method can acquire satisfactory results when compared with traditional methods.
机译：近年来，频带选择已成为一种流行的方法，它可以在保留目标检测和分类分析所需的信息的同时，降低高光谱数据的维数。这封信提出了一种通过将高光谱数据转换为复杂网络来进行无监督波段选择的新方法。通过分析与每个频带相对应的网络拓扑特征，可以轻松评估信号的统计特性和固有特性。所提出的方法搜索最适合用于区分和识别不同物质特征的网络集，然后将网络集的相应频段视为所描述的输出结果。该网络度量是频带选择的新标准。实验结果表明，与传统方法相比，该方法可以获得满意的结果。

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