Synthesis of Synthetic Hyperspectral Images with Controllable Spectral Variability Using a Generative Adversarial Network

Synthesis of Synthetic Hyperspectral Images with Controllable Spectral Variability Using a Generative Adversarial Network

In hyperspectral unmixing (HU), spectral variability in hyperspectral images (HSIs) is a major challenge which has received a lot of attention over the last few years. Here, we propose a method utilizing a generative adversarial network (GAN) for creating synthetic HSIs having a controllable degree...

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Bibliographic Details
Main Authors: Burkni Palsson, Magnus O. Ulfarsson, Johannes R. Sveinsson
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Remote Sensing
Subjects:
hyperspectral unmixing
synthetic hyperspectral images
generative adversarial network
variational autoencoder
deep learning
neural network
Online Access:https://www.mdpi.com/2072-4292/15/16/3919

Internet

https://www.mdpi.com/2072-4292/15/16/3919

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