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

Authors

  • Mateus Habermann Universite de Technologie de Compiegne
  • Vincent Frémont
  • Elcio Hideiti Shiguemori

DOI:

https://doi.org/10.52638/rfpt.2018.419

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.

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Published

2018-09-21

How to Cite

Habermann, M., Frémont, V., & Shiguemori, E. H. (2018). Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network. Revue Française de Photogrammétrie et de Télédétection, (217-218), 33–42. https://doi.org/10.52638/rfpt.2018.419

Issue

Section

Meilleurs articles CFPT 2018