End-to-End Convolutional Autoencoder for Nonlinear Hyperspectral Unmixing

Hyperspectral Unmixing is the process of decomposing a mixed pixel into its pure materials (endmembers) and estimating their corresponding proportions (abundances). Although linear unmixing models are more common due to their simplicity and flexibility, they suffer from many limitations in real worl...

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Principais autores:	Mohamad Dhaini, Maxime Berar, Paul Honeine, Antonin Van Exem
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2022-07-01
סדרה:	Remote Sensing
נושאים:	convolutional neural network autoencoder hyperspectral imaging nonlinear spectral unmixing
גישה מקוונת:	https://www.mdpi.com/2072-4292/14/14/3341
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!