Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network

Mateus Habermann, V. Fremont, E. H. Shiguemori
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引用次数: 3

Abstract

Hyperspectral images provide rich  spectral details of the observed scene by exploiting contiguous bands.But, the processing of such images becomes heavy, due to the high dimensionality.Thus, band selection is a practice that has been adopted before any further processing takes place.Therefore, in this paper, a new unsupervised method for band selection based on clustering and neural network is proposed. A comparison with six other band selection frameworks shows the strength of the proposed method.
基于聚类和单层神经网络的无监督高光谱波段选择
高光谱图像通过利用连续波段提供观测场景丰富的光谱细节。但是,由于这些图像的高维数,使其处理变得非常繁重。因此,波段选择是在进行任何进一步处理之前采用的一种做法。为此,本文提出了一种基于聚类和神经网络的无监督波段选择方法。与其他六种波段选择框架的比较表明了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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