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An Iterative Method for Tensor Inpainting Based on Higher-Order Singular Value Decomposition

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Abstract

We consider the problem of tensor (i.e., multidimensional array) inpainting in this paper. By using higher-order singular value decomposition, we propose an iterative algorithm that performs soft thresholding on entries of the core tensor and then reconstructs via the directional orthogonal matrices. An inpainted tensor is obtained at the end of the iteration. Simulations conducted over color images, video frames, and MR images validate that the proposed algorithm is competitive with state-of-the-art completion algorithms. The evaluation is made in terms of quality metrics and visual comparison.

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Authors and Affiliations

  1. Electrical and Electronic Engineering Department, Eastern Mediterranean University, Gazimagusa, via Mersin 10, Turkey

    S. F. Yeganli, R. Yu & H. Demirel

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  1. S. F. Yeganli
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  2. R. Yu
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Correspondence to S. F. Yeganli.

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Yeganli, S.F., Yu, R. & Demirel, H. An Iterative Method for Tensor Inpainting Based on Higher-Order Singular Value Decomposition. Circuits Syst Signal Process 37, 3827–3841 (2018). https://doi.org/10.1007/s00034-017-0732-1

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  • DOI: https://doi.org/10.1007/s00034-017-0732-1

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