Noise removal with Gauss curvature-driven diffusion

Author

Lee, Suk-ho ; Seo, Jin Keun

Author_Institution

Dept. of Math., Yonsei Univ., Seoul, South Korea

Volume

14

Issue

7

fYear

2005

fDate

7/1/2005 12:00:00 AM

Firstpage

904

Lastpage

909

Abstract

In this paper, we propose the use of the Gauss curvature in a Gauss curvature-driven diffusion equation for noise removal. The proposed scheme uses the Gauss curvature as the conductance term and controls the amount of diffusion. The main advantage of the scheme is that it preserves important structures, such as straight edges, curvy edges, ramps, corners, small-scaled features, etc.

Keywords

Gaussian processes; image denoising; partial differential equations; Gauss curvature-driven diffusion equation; conductance term; image processing; noise removal; nonlinear partial differential equation; Biomedical imaging; Gaussian noise; Gaussian processes; Image restoration; Level set; Mathematics; Noise level; Nonlinear equations; Partial differential equations; Gauss curvature; noise removal; nonlinear partial differential equation (PDE); Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Models, Statistical; Normal Distribution; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2005.849294

Filename

1439563