uDAS: An Untied Denoising Autoencoder With Sparsity for Spectral Unmixing

Linear spectral unmixing is the practice of decomposing the mixed pixel into a linear combination of the constituent endmembers and the estimated abundances. This paper focuses on unsupervised spectral unmixing where the endmembers are unknown a priori . Conventional approaches use either geometrica...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing Vol. 57; no. 3; pp. 1698 - 1712
Main Authors:	Qu, Ying, Qi, Hairong
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.03.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Cascading Collaboration Decoding Deep learning denoising autoencoder Estimation hyperspectral image (HSI) Machine learning Matrix decomposition Minimization Network management systems Noise reduction Optimization Reconstruction Sparsity Spectra spectral unmixing
ISSN:	0196-2892, 1558-0644
Online Access:	Get full text
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