Title :
Noise removal with Gauss curvature-driven diffusion
Author :
Lee, Suk-ho ; Seo, Jin Keun
Author_Institution :
Dept. of Math., Yonsei Univ., Seoul, South Korea
fDate :
7/1/2005 12:00:00 AM
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;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2005.849294