Hyperspectral Band Selection: A Review

A hyperspectral imaging sensor collects detailed spectral responses from ground objects using hundreds of narrow bands; this technology is used in many real-world applications. Band selection aims to select a small subset of hyperspectral bands to remove spectral redundancy and reduce computational costs while preserving the significant spectral information of ground objects. In this article, we review current hyperspectral band selection methods, which can be classified into six main categories: ranking based, searching based, clustering based, sparsity based, embedding -learning based, and hybrid-scheme based. With two widely used hyperspectral data sets, we illustrate the classification performances of…

• NN
  National Natural Science Foundation of China

  Awards: U1609203, 41671342
• NS
  Natural Science Foundation of Ningbo

  Award: 2017A610294