Robust principal component pursuit via inexact alternating minimization on matrix manifolds

DOI10.1007/s10851-014-0527-yzbMath1329.15056OpenAlexW1976218807WikidataQ115155137 ScholiaQ115155137MaRDI QIDQ2515360

Michael Hintermüller, Tao Wu

Publication date: 31 July 2015

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: http://edoc.hu-berlin.de/18452/14349

zbMATH Keywords

image processingRiemannian manifoldsparse matrixmatrix decompositionlow-rank matrixalternating minimizationoptimization on manifolds

Mathematics Subject Classification ID

Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Methods of local Riemannian geometry (53B21) Matrix completion problems (15A83)

Related Items

Efficient and robust background modeling with dynamic mode decomposition ⋮ A Second Order Nonsmooth Variational Model for Restoring Manifold-Valued Images

Uses Software

• PROPACK
• Manopt
• LMaFit
• RTRMC

Cites Work

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