Novel methods for multilinear data completion and de-noising based on tensor-SVD

CVPR 2014 Zemin ZhangGregory ElyShuchin AeronNing HaoMisha Kilmer

In this paper we propose novel methods for completion (from limited samples) and de-noising of multilinear (tensor) data and as an application consider 3-D and 4- D (color) video data completion and de-noising. We exploit the recently proposed tensor-Singular Value Decomposition (t-SVD)[11]... (read more)

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