Abstract
Multiplicative noise removal technology is very useful in many applications. In this paper, we propose a new multiplicative noise removal algorithm using TVL1 norm and adaptive penalty parameter. We use TVL1 norm as the data term and we incorporate the modified total variation regularization term in the objective function to deal with multiplicative noise. The balance of fidelity term and regularization term can be changed in different areas with different gray value. We modify the penalty parameter using facet model and we call it as adaptive penalty parameter. Thus in iterating procedure, our method can change the degree of noise removal in different areas with different noise level adaptively. The results show the outperforming effect of our method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.