Robust Low-Rank Tensor Minimization via a New Tensor Spectral k -Support Norm

Recently, based on a new tensor algebraic framework for third-order tensors, the tensor singular value decomposition (t-SVD) and its associated tubal rank definition have shed new light on low-rank tensor modeling. Its applications to robust image/video recovery and background modeling show promisin...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 29; S. 2314 - 2327
Hauptverfasser:	Lou, Jian, Cheung, Yiu-Ming
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.01.2020
Schlagworte:	alternating direction method of multipliers Computational modeling Computer science Computer vision conditional gradient descent Minimization Optimization proximal algorithm Robust low-rank tensor minimization Task analysis tensor robust principal component analysis tensor singular value decomposition (t-SVD)
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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