Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion

The main aim of this paper is to study quaternion matrix factorization for low-rank quaternion matrix completion and its applications in color image processing. For the real-world color images, we proposed a novel model called low-rank quaternion matrix completion (LRQC), which adds total variation...

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Main Authors: Jiang-Feng Chen, Qing-Wen Wang, Guang-Jing Song, Tao Li
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/11/9/2144
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author Jiang-Feng Chen
Qing-Wen Wang
Guang-Jing Song
Tao Li
author_facet Jiang-Feng Chen
Qing-Wen Wang
Guang-Jing Song
Tao Li
author_sort Jiang-Feng Chen
collection DOAJ
description The main aim of this paper is to study quaternion matrix factorization for low-rank quaternion matrix completion and its applications in color image processing. For the real-world color images, we proposed a novel model called low-rank quaternion matrix completion (LRQC), which adds total variation and Tikhonov regularization to the factor quaternion matrices to preserve the spatial/temporal smoothness. Moreover, a proximal alternating minimization (PAM) algorithm was proposed to tackle the corresponding optimal problem. Numerical results on color images indicate the advantages of our method.
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spelling doaj.art-cf66702097c64d53829043287d3e5f7c2023-11-17T23:20:35ZengMDPI AGMathematics2227-73902023-05-01119214410.3390/math11092144Quaternion Matrix Factorization for Low-Rank Quaternion Matrix CompletionJiang-Feng Chen0Qing-Wen Wang1Guang-Jing Song2Tao Li3Department of Mathematics, Shanghai University, Shanghai 200444, ChinaDepartment of Mathematics, Shanghai University, Shanghai 200444, ChinaSchool of Mathematics and Information Sciences, Weifang University, Weifang 261061, ChinaKey Laboratory of Engineering Modeling and Statistical Computation of Hainan Province, Department of Mathematics, Hainan University, Haikou 570228, ChinaThe main aim of this paper is to study quaternion matrix factorization for low-rank quaternion matrix completion and its applications in color image processing. For the real-world color images, we proposed a novel model called low-rank quaternion matrix completion (LRQC), which adds total variation and Tikhonov regularization to the factor quaternion matrices to preserve the spatial/temporal smoothness. Moreover, a proximal alternating minimization (PAM) algorithm was proposed to tackle the corresponding optimal problem. Numerical results on color images indicate the advantages of our method.https://www.mdpi.com/2227-7390/11/9/2144low-rank quaternion matrix factorizationquaternion matrix completionproximal alternating minimizationcolor image restoration
spellingShingle Jiang-Feng Chen
Qing-Wen Wang
Guang-Jing Song
Tao Li
Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
Mathematics
low-rank quaternion matrix factorization
quaternion matrix completion
proximal alternating minimization
color image restoration
title Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
title_full Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
title_fullStr Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
title_full_unstemmed Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
title_short Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
title_sort quaternion matrix factorization for low rank quaternion matrix completion
topic low-rank quaternion matrix factorization
quaternion matrix completion
proximal alternating minimization
color image restoration
url https://www.mdpi.com/2227-7390/11/9/2144
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AT qingwenwang quaternionmatrixfactorizationforlowrankquaternionmatrixcompletion
AT guangjingsong quaternionmatrixfactorizationforlowrankquaternionmatrixcompletion
AT taoli quaternionmatrixfactorizationforlowrankquaternionmatrixcompletion