A New Nonlinear Diffusion Equation Model for Noisy Image Segmentation. (9th March 2016)
- Record Type:
- Journal Article
- Title:
- A New Nonlinear Diffusion Equation Model for Noisy Image Segmentation. (9th March 2016)
- Main Title:
- A New Nonlinear Diffusion Equation Model for Noisy Image Segmentation
- Authors:
- Chen, Bo
Zhou, Xiao-Hui
Zhang, Li-Wei
Wang, Jie
Zhang, Wei-Qiang
Zhang, Chen - Other Names:
- Weder Ricardo Academic Editor.
- Abstract:
- 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.
- Is Part Of:
- Advances in mathematical physics. Volume 2016(2016)
- Journal:
- Advances in mathematical physics
- Issue:
- Volume 2016(2016)
- Issue Display:
- Volume 2016, Issue 2016 (2016)
- Year:
- 2016
- Volume:
- 2016
- Issue:
- 2016
- Issue Sort Value:
- 2016-2016-2016-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-03-09
- Subjects:
- Mathematical physics -- Periodicals
Mathematical physics
Periodicals
530.15 - Journal URLs:
- http://www.hindawi.com/journals/amp/contents.html ↗
http://bibpurl.oclc.org/web/44179 ↗ - DOI:
- 10.1155/2016/8745706 ↗
- Languages:
- English
- ISSNs:
- 1687-9120
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 10295.xml