Low Rank and Total Variation Based Two-Phase Method for Image Deblurring with Salt-and-Pepper Impulse Noise
Year: 2023
Author: Shirong Deng, Tieyong Zeng, Yuchao Tang, Shirong Deng, Tieyong Zeng
Numerical Mathematics: Theory, Methods and Applications, Vol. 16 (2023), Iss. 4 : pp. 1013–1034
Abstract
Although there are many effective methods for removing impulse noise in image restoration, there is still much room for improvement. In this paper, we propose a new two-phase method for solving such a problem, which combines the nuclear norm and the total variation regularization with box constraint. The popular alternating direction method of multipliers and the proximal alternating direction method of multipliers are employed to solve this problem. Compared with other algorithms, the obtained algorithm has an explicit solution at each step. Numerical experiments demonstrate that the proposed method performs better than the state-of-the-art methods in terms of both subjective and objective evaluations.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/nmtma.OA-2022-0190
Numerical Mathematics: Theory, Methods and Applications, Vol. 16 (2023), Iss. 4 : pp. 1013–1034
Published online: 2023-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 22
Keywords: Image deblurring impulse noise total variation nuclear norm.