A Fast Volume-Gradient-Based Band Selection Method for Hyperspectral Image
A Fast Volume-Gradient-Based Band Selection Method for Hyperspectral Image
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DOI：
10.1109/tgrs.2014.2307880
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发表时间：
2014-11-01
影响因子：
8.2
通讯作者：
Zhao, Yongchao
中科院分区：
文献类型：
--
作者：
Geng, Xiurui;Sun, Kang;Zhao, Yongchao
本文研究了超光谱图像中次单纯形的体积与单纯形的体积梯度之间的关系。利用这种关系，我们提出了一种有效的波段选择方法，即基于体积梯度的波段选择方法(VGBS)。VGBS方法是一种无监督的方法，它试图连续地去除最多的冗余波段。有趣的是，VGBS方法不需要计算所有子单形的体积，而是只根据体积的梯度来找到最冗余的频带。对模拟和真实高光谱数据的实验验证了该方法的有效性。
In this paper, a subtle relationship is found between the volume of a subsimplex and the volume gradient of a simplex with respect to hyperspectral images. By using this relationship, we propose an efficient band selection method, namely, the volume-gradient-based band selection (VGBS) method. The VGBS method is an unsupervised method, which tries to remove the most redundant band successively. Interestingly, the VGBS method can find the most redundant band based only on the gradient of volume instead of calculating the volumes of all subsimplexes. Experiments on simulated and real hyperspectral data verify the efficiency of the proposed method.