Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition

Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition Publisher

Sedighin F^{1, 2} ; Cichocki A^{2, 3}

Show Affiliations

1. Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
2. Computational and Data Intensive Science and Engineering Department, Skolkovo Institute of Science and Technology (SKOLTECH), Moscow, Russian Federation
3. Systems Research Institute, Polish Academy of Science, Warsaw, Poland

Source: Frontiers in Artificial Intelligence Published:2021

Abstract

Tensor Completion is an important problem in big data processing. Usually, data acquired from different aspects of a multimodal phenomenon or different sensors are incomplete due to different reasons such as noise, low sampling rate or human mistake. In this situation, recovering the missing or uncertain elements of the incomplete dataset is an important step for efficient data processing. In this paper, a new completion approach using Tensor Ring (TR) decomposition in the embedded space has been proposed. In the proposed approach, the incomplete data tensor is first transformed into a higher order tensor using the block Hankelization method. Then the higher order tensor is completed using TR decomposition with rank incremental and multistage strategy. Simulation results show the effectiveness of the proposed approach compared to the state of the art completion algorithms, especially for very high missing ratios and noisy cases. © Copyright © 2021 Sedighin and Cichocki.

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Experts (# of related papers)

Farnaz Sedighin (3)

Hossein Rabbani (1)

Style	Citing Format
MLA	Sedighin F, Cichocki A. "Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition." Frontiers in Artificial Intelligence, vol. 4, no. , 2021, pp. -.
APA	Sedighin F, Cichocki A (2021). Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition. Frontiers in Artificial Intelligence, 4(), -.
Chicago	Sedighin F, Cichocki A. "Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition." Frontiers in Artificial Intelligence 4, no. (2021): -.
Harvard	Sedighin F, Cichocki A (2021) 'Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition', Frontiers in Artificial Intelligence, 4(), pp. -.
Vancouver	Sedighin F, Cichocki A. Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition. Frontiers in Artificial Intelligence. 2021;4():-.
BibTex	@article{ author = {Sedighin F and Cichocki A}, title = {Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition}, journal = {Frontiers in Artificial Intelligence}, volume = {4}, number = {}, pages = {-}, year = {2021} }
RIS	TY - JOUR AU - Sedighin F AU - Cichocki A TI - Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition JO - Frontiers in Artificial Intelligence VL - 4 IS - SP - EP - PY - 2021 ER -

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