Release Time:2019-03-13  Hits:

Indexed by: Journal Article

Date of Publication: 2019-01-01

Journal: IEEE TRANSACTIONS ON IMAGE PROCESSING

Included Journals: Scopus、SCIE

Volume: 28

Issue: 1

Page Number: 170-180

ISSN: 1057-7149

Key Words: Tensor completion; one bit observation; TNN-norm; alternating direction method of multipliers (ADMM)

Abstract: The tensor completion issues have obtained a great deal of attention in the past few years. However, the data fidelity part minimizes a squared loss function, which may be inappropriate for the case of noisy one-bit observations. In this paper, we alleviate the mentioned difficulty by drawing on the experience of matrix scenarios. Based on the convex relation to L-1 norm of the tensor multi-rank, we propose a novel optimization model trying to recover the underlying tensor in case of one-bit observations. The feasibility of this model is proved by theoretical derivations. Furthermore, an alternating direction method of multipliers based algorithm is designed to find the solution. The numerical experiments demonstrate the effectiveness of our method.