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Advances in Mathematical Physics
Volume 2016, Article ID 8745706, 7 pages
http://dx.doi.org/10.1155/2016/8745706
Research Article

A New Nonlinear Diffusion Equation Model for Noisy Image Segmentation

1College of Mathematics and Statistics, Shenzhen University, Shenzhen 518060, China
2Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen 518060, China
3School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350116, China
4College of Computer Science and Technology, Beijing University of Technology, Beijing 100124, China

Received 3 September 2015; Revised 21 December 2015; Accepted 3 January 2016

Academic Editor: Ricardo Weder

Copyright © 2016 Bo Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Image segmentation and image denoising are two important and fundamental topics in the field of image processing. Geometric active contour model based on level set method can deal with the problem of image segmentation, but it does not consider the problem of image denoising. In this paper, a new diffusion equation model for noisy image segmentation is proposed by incorporating some classical diffusion equation denoising models into the segmental process. An assumption about the connection between the image intensity and level set function is given firstly. Some classical denoising models are employed to describe the evolution of level set function secondly. The final nonlinear diffusion equation model for noisy image segmentation is built thirdly. Then image segmentation and image denoising are combined in a united framework. The segmental results can be presented by level set function. Experimental results show that the new model has the advantage of noise resistance and is superior to traditional segmentation model.