Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network
Mateus Habermann, Vincent Frémont, Elcio Hideiti Shiguemori
Revue Française de Photogrammétrie et de Télédétection · 2018
doi:10.52638/rfpt.2018.419 (opens in a new tab)
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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.
Abstract licence: CC BY
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