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基于广义模糊吉波斯随机场的噪声图象分割 被引量：2

Noise image segmentation based on generalized fuzzy Gibbs random field
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摘要 基于吉波斯随机场分割模型的图象分割方法是一种常用的重要方法。本文结合广义模糊集理论,针对噪声大的模糊图象分割问题,重新定义了吉波斯场的集团势函数,将广义模糊隶属度引入势函数,建立了新的分割模型。在此基础上用条件迭代模式(ICM)法对图象进行了优化分割。实验表明,该方法能有效地分割退化的模糊图象。 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.
作者 龚剑 张煜 陈武凡
机构地区 南方医科大学生物医学工程学院
出处 《南方医科大学学报》 CAS CSCD 北大核心 2006年第4期390-393,共4页 Journal of Southern Medical University
基金 国家"973"项目(2003CB716103) 广东省自然科学基金(032888)~~
关键词 吉波斯随机场 集团势函数 广义模糊集 条件迭代模式 Gibbs random field clique potential function generalized fuzzy set iterative conditional modes
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献8

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同被引文献13

  • 1高贵,匡纲要,李德仁.高分辨率SAR图像分割及目标特征提取[J].宇航学报,2006,27(2):238-244. 被引量：18
  • 2陈功,张雄伟,邓玉良.基于HMM与K-均值聚类的声目标识别[J].弹箭与制导学报,2006,26(2):144-147. 被引量：5
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  • 7Sridharan K, Govindaraju V. A sampling based approach to facial feature extraction [C] // Fourth IEEE Workshop on Automatic Identification Advanced Technologies. New York: IEEE Press, 2005: 51.
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引证文献2

二级引证文献5

南方医科大学学报
2006年 第4期

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