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基于广义模糊吉布斯随机场的噪声图像分割

[Noise image segmentation based on generalized fuzzy Gibbs random field].

作者信息

Gong Jian, Zhang Yu, Chen Wu-fan

机构信息

Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.

出版信息

Nan Fang Yi Ke Da Xue Xue Bao. 2006 Apr;26(4):390-3.

Abstract

In order to segment the blurred image with large noise, the authors propose a new Bayesian image segmentation method based on generalized fuzzy Gibbs random field. Based on the generalized fuzzy set, the new method introduces generalized fuzzy membership into Gibbs potential function and the potential function is redefined to obtain the new segmentation model. The optimal processing is executed through iterative conditional modes (ICM). The experiment results showed that the new approach could effectively segment the degenerated images.

摘要

为了分割噪声较大的模糊图像,作者提出了一种基于广义模糊吉布斯随机场的贝叶斯图像分割新方法。该新方法基于广义模糊集,将广义模糊隶属度引入吉布斯势函数,并重新定义势函数以获得新的分割模型。通过迭代条件模式(ICM)进行最优处理。实验结果表明,该新方法能够有效地分割退化图像。

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