CTNet: an efficient coupled transformer network for robust hyperspectral unmixing

This study introduces the coupled transformer Network (CTNet), an architecture designed to enhance the robustness and effectiveness of hyperspectral unmixing (HSU) tasks, addressing key limitations of traditional autoencoder (AE) frameworks. Traditional AEs, consisting of an encoder and a decoder, e...

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Bibliographic Details
Published in:	International journal of remote sensing Vol. 45; no. 17; pp. 5679 - 5712
Main Authors:	Meng, Fanlei, Sun, Haixin, Li, Jie, Xu, Tingfa
Format:	Journal Article
Language:	English
Published:	London Taylor & Francis 01.09.2024 Taylor & Francis Ltd
Subjects:	Abundance Artificial neural networks Coders Coupled transformer network cross-attention data collection Effectiveness Estimates image analysis Pixels Reconstruction robust hyperspectral unmixing Robustness (mathematics) spectral variability transcription loss Transformers uncertainty
ISSN:	0143-1161, 1366-5901, 1366-5901
Online Access:	Get full text
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