Quaternion Matrix Factorization for Low-Rank Quaternion Matrix Completion
نویسندگان
چکیده
The main aim of this paper is to study quaternion matrix factorization for low-rank completion and its applications in color image processing. For the real-world images, we proposed a novel model called (LRQC), which adds total variation Tikhonov regularization factor matrices preserve spatial/temporal smoothness. Moreover, proximal alternating minimization (PAM) algorithm was tackle corresponding optimal problem. Numerical results on images indicate advantages our method.
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ژورنال
عنوان ژورنال: Mathematics
سال: 2023
ISSN: ['2227-7390']
DOI: https://doi.org/10.3390/math11092144