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噪声图像分割的全局凸优化变分模型
引用本文:陈杰,潘振宽,魏伟波. 噪声图像分割的全局凸优化变分模型[J]. 青岛大学学报(自然科学版), 2012, 25(1): 57-62,67
作者姓名:陈杰  潘振宽  魏伟波
作者单位:青岛大学信息工程学院,山东青岛,266071
摘    要:基于二值标记函数及图像噪声分布模型建立了两相图像分割的全局凸优化变分模型。其能量泛函的数据项基于通用的概率分布函数,分割轮廓线的长度用标记函数的总变差近似。在交替优化过程中,当区域参数估计出后,采用凸松弛和阈值化技术计算标记函数实现全局优化,并设计了该全局凸优化模型的快速Split Bregman算法。作为实例,本文实现了基于高斯分布、瑞利分布、泊松分布及伽马分布模型的两相图像分割。

关 键 词:图像分割  二值标记函数  全局凸优化  参数估计

A Global Variational Model of Image Segmentation for Images with Noises
CHEN Jie , PAN Zhen-kuan , WEI Wei-bo. A Global Variational Model of Image Segmentation for Images with Noises[J]. Journal of Qingdao University(Natural Science Edition), 2012, 25(1): 57-62,67
Authors:CHEN Jie    PAN Zhen-kuan    WEI Wei-bo
Affiliation:(College of Information Engineering,Qingdao University,Qingdao 266071,China)
Abstract:A general model of two phase segmentation of images with noises based on binary label function and convex relaxation method is proposed.Its region model is based on the general probability distribution functions including Gaussian,Rayleigh,Poisson and Gamma distribution,and so on.The length term of active contour model is approximated using the total variation of the binary function.In the alternate process of optimization the parameters are estimated.The global minimization is realized via convexification and thresholding techniques,and the Split Bregman algorithm is designed.
Keywords:Image segmentation  Binary label function  Global minimization  Parameter estimation
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