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Improved weighted nuclear norm with total variation for removing multiplicative noise

Authors :
Jiyu Kong
Xujiao Liu
Suyu Liu
Weigang Sun
Source :
AIP Advances, Vol 14, Iss 6, Pp 065206-065206-10 (2024)
Publication Year :
2024
Publisher :
AIP Publishing LLC, 2024.

Abstract

This paper introduces an improved weighted nuclear norm with a total variation model tailored for removing multiplicative noise. The model incorporates a weight matrix to regularize the residual matrix, effectively leveraging image redundancy to differentiate various statistical properties of the noise. Since there is no guarantee of a unique solution, the model is reformulated as a linear equality constraint problem and decomposed into two subproblems. These are addressed by using the alternating direction method of multipliers and the split Bregman method, respectively. In addition, each alternative update step has a closed-form and convergent solution. After obtaining the denoised image in the log-domain, the recovered image is given by using the exponential function and bias correction. Experimental evaluations demonstrate the efficacy of our algorithms in enhancing image restoration quality.

Subjects

Subjects :
Physics
QC1-999

Details

Language :
English
ISSN :
21583226
Volume :
14
Issue :
6
Database :
Directory of Open Access Journals
Journal :
AIP Advances
Publication Type :
Academic Journal
Accession number :
edsdoj.38c42010c97849b1a6f9dd64a5efa52e
Document Type :
article
Full Text :
https://doi.org/10.1063/5.0206599