A variant beltrami flow for multiplicative noise removal

Author

Li, Fang ; Liu, Ruihua

Author_Institution

Dept. of Math., East China Normal Univ., Shanghai, China

Volume

2

fYear

2011

fDate

10-12 June 2011

Firstpage

237

Lastpage

241

Abstract

In this paper, we propose a new diffusion approach for multiplicative noise removal. The diffusion is driven by two terms. One is the regularization term which comes from the Beltrami flow, the other is the fidelity term inspired by the Aubert-Aujol (AA) model. The two terms are balanced by a weight parameter. In order to overcome the difficulty in choosing the best weight, we derive an automatic scheme. Numerical results show that the proposed method preserves edges better than the scalar AA model while smoothing out the multiplicative noise.

Keywords

gradient methods; image denoising; maximum likelihood estimation; Aubert-Aujol model; Rudin-Osher-Fatemi model; diffusion approach; edge preservation; gradient descent flow; image denoising; maximum a posterior estimation; multiplicative noise removal; variant Beltrami flow; Computational modeling; Image edge detection; Manifolds; Mathematical model; Noise; Noise reduction; Numerical models; AA model; Beltrami flow; SNR; multiplicative noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-8727-1

Type

conf

DOI

10.1109/CSAE.2011.5952461

Filename

5952461