Image Segmentation and Selective Smoothing Based on Variational Framework

doi:10.1007/s11265-008-0248-9

	Image Segmentation and Selective Smoothing Based on Variational Framework
	Chen, Bo 1; Yuen, Pong C.2; Lai, Jian-Huang 3,4; Chen, Wen-Sheng 1,5
刊名	JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
	2009-03-01
卷号	54 期号:1-3 页码:145-158
关键词	Image segmentation Image smoothing Variational framework Active contour model Fourth-order PDE model Median filtering
ISSN号	1939-8018
DOI	10.1007/s11265-008-0248-9
英文摘要	This paper addresses the segmentation and smoothing problems in biomedical imaging under variational framework. In order to get better results, this paper proposes a new segmentation and selective smoothing algorithm. This paper has the following three contributions. First, a new statistical active contour model (SACM) is introduced for noisy image segmentation. SACM is proposed to solve the problem in fast edge integration (FEI) method, which takes advantages of both edge-based and region-based active contour model but only considers the mean information inside and outside of the evolution curve. In SACM, a new statistical term for considering the probability distribution density of regions and a unified variational framework are proposed for construction of different segmentation models with different probability density functions. Moreover, a penalized term is also introduced in the proposed model as internal energy in order to avoid the time consuming re-initialization process. Second, a new symmetric fourth-order PDE denoising algorithm is developed to avoid the blocky effects in second-order PDE model, while preserving edges. Third, in each stage of segmentation process, different denoising algorithms (or different parameters in the same denoising model) can be employed for different sub-regions independently, so that better segmentation and smoothing results can be obtained. Compared with existing methods, our method is more flexible, robust to noise, computationally efficient and produces better results.
资助项目	NSFC[60675016] ; NSFC[60633030] ; 973 Program[2006CB303104] ; NSF of Guangdong[06023194] ; NSF of Guangdong[06105776] ; SZU R/D
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000265085600013
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/8684]
专题	中国科学院数学与系统科学研究院
通讯作者	Chen, Bo
作者单位	1.Shenzhen Univ, Coll Math & Computat Sci, Shenzhen, Peoples R China 2.Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China 3.Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China 4.Guangdong Prov Key Lab Informat Secur, Guangzhou, Guangdong, Peoples R China 5.CAS, Key Lab Math Mechanizat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Chen, Bo,Yuen, Pong C.,Lai, Jian-Huang,et al. Image Segmentation and Selective Smoothing Based on Variational Framework[J]. JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY,2009,54(1-3):145-158.
APA	Chen, Bo,Yuen, Pong C.,Lai, Jian-Huang,&Chen, Wen-Sheng.(2009).Image Segmentation and Selective Smoothing Based on Variational Framework.JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY,54(1-3),145-158.
MLA	Chen, Bo,et al."Image Segmentation and Selective Smoothing Based on Variational Framework".JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 54.1-3(2009):145-158.