A Fast Volume-Gradient-Based Band Selection Method for Hyperspectral Image

作者:Geng Xiurui*; Sun Kang; Ji Luyan; Zhao Yongchao
来源:IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(11): 7111-7119.
DOI:10.1109/TGRS.2014.2307880

摘要

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.

  • 出版日期2014-11
  • 单位中国科学院

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