Image smoothing model based on the combination of the gradient and curvature

被引:2
作者
Zhou Xian-Chun [1 ,2 ,3 ]
Wang Mei-Ling [1 ,2 ,3 ]
Shi Lan-Fang [4 ]
Zhou Lin-Feng [1 ,2 ,3 ]
Wu Qin [1 ,2 ,3 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Coll Elect & Informat Engn, Nanjing 210044, Jiangsu, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210044, Jiangsu, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Meteorol Observat & Informat Proc, Nanjing 210044, Jiangsu, Peoples R China
[4] Nanjing Univ Informat Sci & Technol, Coll Math & Stat, Nanjing 210044, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
combination of gradient and curvature; curvature; image smoothing; image denosing; EDGE-DETECTION; NONLINEAR DIFFUSION;
D O I
10.7498/aps.64.044201
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In image processing, in order to keep the detailed information about image edge, we propose a curvature smoothing model based on the nature of diffusion coefficient and curvature. Considering the fact that the curvature will change significantly when the image is affected by noise pollution, in this article we will continue to take the level set curvature as a detection factor and substitute it into the model, then we present a new model which combines gradient and curvature. Analysis and simulation indicate that the new model can keep more image information than the Perona-Malik model, and it can strengthen the sharp edge of the image efficiently, and well keep the straight lines of image, and edges, corners, slopes and small-scale features of curve at the same time, so this model is an ideal model.
引用
收藏
页数:7
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