Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion

Jiang-Feng Chen, Qing-Wen Wang (), Guang-Jing Song and Tao Li
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Jiang-Feng Chen: Department of Mathematics, Shanghai University, Shanghai 200444, China
Qing-Wen Wang: Department of Mathematics, Shanghai University, Shanghai 200444, China
Guang-Jing Song: School of Mathematics and Information Sciences, Weifang University, Weifang 261061, China
Tao Li: Key Laboratory of Engineering Modeling and Statistical Computation of Hainan Province, Department of Mathematics, Hainan University, Haikou 570228, China

Mathematics, 2023, vol. 11, issue 9, 1-13

Abstract: 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.

Keywords: low-rank quaternion matrix factorization; quaternion matrix completion; proximal alternating minimization; color image restoration (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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