A new efficient variational model for multiplicative noise removal

ABSTRACT

In this paper, based on the approximation of the Taylor expansion, a novel fidelity term is formulated. We propose a new variational image restoration model to recover an image from its multiplicative noised version. We show that the proposed model is strictly convex and has a unique solution so that the model can be performed by the primal–dual method. Compared with other models, the proposed model is able to not only deal with various problems of different type noises, such as the multiplicative Beta noise, F noise, Gaussian noise, but also take significantly less computational time.

KEYWORDS:

• Primal–dual method
• multiplicative noise
• Taylor approximation model
• variational model
• semi-implicit iteration
• strictly convex

2010 MATHEMATICS SUBJECT CLASSIFICATIONS:

• 49M20
• 49N45
• 65K10
• 90C90

Acknowledgments

The author would like to sincerely thank the reviewers for their valuable and constructive comments. The author would like to sincerely thank the authors of [17] and [10] for sharing their source codes.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work is supported by the NSFC of China (Nos.11531005 and 91330101).