A new diffusion-based variational model for image denoising and segmentation

被引：13
|
作者：
Li, Fang [1 ]
Shen, Chaomin
Pi, Ling
机构：
[1] E China Normal Univ, Dept Math, Shanghai 200062, Peoples R China
[2] South West Univ, Dept Math, Chongqing 400715, Peoples R China
[3] E China Normal Univ, Joint Lab Imaging Sci & Technol, Shanghai 200062, Peoples R China
[4] E China Normal Univ, Dept Comp Sci, Shanghai 200062, Peoples R China
[5] Shanghai Jiao Tong Univ, Dept Appl Math, Shanghai 200030, Peoples R China
来源：
JOURNAL OF MATHEMATICAL IMAGING AND VISION | 2006年 / 26卷 / 1-2期
关键词：
image denoising; segmentation; bounded variation function; Ginzburg-Landau model; heat flow;
D O I：
10.1007/s10851-006-8303-2
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 a new variational model for image denoising and segmentation of both gray and color images. This method is inspired by the complex Ginzburg-Landau model and the weighted bounded variation model. Compared with active contour methods, our new algorithm can detect non-closed edges as well as quadruple junctions, and the initialization is completely automatic. The existence of the minimizer for our energy functional is proved. Numerical results show the effectiveness of our proposed model in image denoising and segmentation.
引用
收藏
页码：115 / 125
页数：11
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