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

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

Résumé

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.
Publiée
2018-09-21
Comment citer
HABERMANN, Mateus; FRÉMONT, Vincent; SHIGUEMORI, Elcio Hideiti. Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network. Revue Française de Photogrammétrie et de Télédétection, [S.l.], n. 217-218, p. 33-42, sep. 2018. ISSN 1768-9791. Disponible à l'adresse : >https://www.sfpt.fr/rfpt/index.php/RFPT/article/view/419>. Date de consultation : 26 août 2019
Rubrique
Meilleurs articles CFPT 2018