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Tensor Factorization-Based Method for Tensor Completion with Spatio-temporal Characterization

Author

Listed:
  • Quan Yu

    (Hunan University)

  • Xinzhen Zhang

    (Tianjin University)

  • Zheng-Hai Huang

    (Tianjin University)

Abstract

In this paper, we propose a novel tensor factorization-based method for the third-order tensor completion problem with spatio-temporal characterization. For this aim, we consider tensor fibered rank, which extends tubal rank, to improve the flexibility and accuracy of data characterization. Based on this rank, we apply a factorization-based method to complete the third-order low-rank tensors with spatio-temporal characteristics, which are intrinsic features of image, video and internet traffic tensor data. The model not only makes good use of the low-rank structure of tensors, but also takes into account the spatio-temporal characteristics of the data. Finally, we report numerical results on completing image, video and internet traffic data. The results demonstrate that our method outperforms some existing methods.

Suggested Citation

  • Quan Yu & Xinzhen Zhang & Zheng-Hai Huang, 2023. "Tensor Factorization-Based Method for Tensor Completion with Spatio-temporal Characterization," Journal of Optimization Theory and Applications, Springer, vol. 199(1), pages 337-362, October.
    • Handle: RePEc:spr:joptap:v:199:y:2023:i:1:d:10.1007_s10957-023-02287-0
    DOI: 10.1007/s10957-023-02287-0
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    References listed on IDEAS

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