Noise removal with Gauss curvature-driven diffusion

被引：76

作者：

Lee, SH ^{[1
]}

Seo, JK ^{[1
]}

机构：

[1] Yonsei Univ, Dept Math, Seoul 120749, South Korea

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2005年 / 14卷 / 07期

关键词：

Gauss curvature; noise removal; nonlinear partial differential equation (PDE;

D O I：

10.1109/TIP.2005.849294

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：904 / 909

页数：6

共 13 条

[1] IMAGE SELECTIVE SMOOTHING AND EDGE-DETECTION BY NONLINEAR DIFFUSION .2. [J].