MyJournals Home  

RSS FeedsRemote Sensing, Vol. 15, Pages 2900: Hyperspectral Unmixing Using Robust Deep Nonnegative Matrix Factorization (Remote Sensing)

 
 

2 june 2023 11:50:08

 
Remote Sensing, Vol. 15, Pages 2900: Hyperspectral Unmixing Using Robust Deep Nonnegative Matrix Factorization (Remote Sensing)
 


Nonnegative matrix factorization (NMF) and its numerous variants have been extensively studied and used in hyperspectral unmixing (HU). With the aid of the designed deep structure, deep NMF-based methods demonstrate advantages in exploring the hierarchical features of complex data. However, a noise corruption problem commonly exists in hyperspectral data and severely degrades the unmixing performance of deep NMF-based methods when applied to HU. In this study, we propose an ℓ2,1 norm-based robust deep nonnegative matrix factorization (ℓ2,1-RDNMF) for HU, which incorporates an ℓ2,1 norm into the two stages of the deep structure to achieve robustness. The multiplicative updating rules of ℓ2,1-RDNMF are efficiently learned and provided. The efficiency of the presented method is verified in experiments using both synthetic and genuine data.


 
62 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 15, Pages 2899: Improved General Polarimetric Model-Based Decomposition for Coherency Matrix (Remote Sensing)
Remote Sensing, Vol. 15, Pages 2901: Synthetic Data Generation for Deep Learning-Based Inversion for Velocity Model Building (Remote Sensing)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten