Noisy image segmentation based on nonlinear diffusion equation model

被引:19
作者
Chen, Bo [1 ]
Li, Yan [1 ]
Cai, Jin-lin [1 ]
机构
[1] Shenzhen Univ, Coll Math & Computat Sci, Shenzhen 518060, Peoples R China
关键词
Curve evolution; Variation calculus technique; Level set; Locally one-dimensional; Active contour model; Nonlinear diffusion equations; ACTIVE CONTOURS;
D O I
10.1016/j.apm.2011.07.073
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper addresses the segmentation problem in noisy image based on nonlinear diffusion equation model and proposes a new adaptive segmentation model based on gray-level image segmentation model. This model also can be extended to the vector value image segmentation. By virtue of the prior information of regions and boundary of image, a framework is established to construct different segmentation models using different probability density functions. A segmentation model exploiting Gauss probability density function is given in this paper. An efficient and unconditional stable algorithm based on locally one-dimensional (LOD) scheme is developed and it is used to segment the gray image and the vector values image. Comparing with existing classical models, the proposed approach gives the best performance. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:1197 / 1208
页数:12
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