| 模糊C-均值聚类图像分割算法的一种改进 |
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| 引用本文： | 李琳,范九伦,赵凤.模糊C-均值聚类图像分割算法的一种改进[J].西安邮电学院学报,2014(5):56-60. |
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| 作者姓名： | 李琳 范九伦 赵凤 |
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| 作者单位： | 西安邮电大学通信与信息工程学院,陕西西安710121 |
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| 基金项目： | 国家自然科学基金资助项目（61102095,61340040）; 陕西省自然科学基础研究基金资助项目（2012JQ8045） |
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| 摘 要： | 针对传统模糊C-均值聚类算法对含噪图像分割时未充分考虑空间信息的问题,提出一种改进的模糊C-均值聚类算法,将图像的局部和非局部两种空间信息引入到模糊C-均值聚类算法的目标函数中,以使两种空间信息在含噪图像分割中发挥互补作用。将改进算法应用于不同含噪图像的分割实验,结果表明图像像素的均方误差均比改进前有所降低。
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| 关 键 词： | 图像分割 模糊C-均值聚类 局部空间信息 非局部空间信息 |
Improvement of fuzzy C-means clustering image segmentation algorithm |
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| LI Lin,FAN Jiulu,ZHAO Feng.Improvement of fuzzy C-means clustering image segmentation algorithm[J].Journal of Xi'an Institute of Posts and Telecommunications,2014(5):56-60. |
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| Authors: | LI Lin FAN Jiulu ZHAO Feng |
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| Affiliation: | (School oI Communication and Information Engineering, Xi＇an University of Posts and Teleconmnunications, Xi＇an 710121, China) |
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| Abstract: | In view of the problem that traditional fuzzy c-means （FCM）clustering segmentation algorithm does not consider the spatial information of noisy image sufficiently,an improved fuzzy c-means （FCM）clustering segmentation algorithm is proposed in this paper.The improved algorithm introduces both local and non-local spatial information into the objective function,and the two spatial information can then play a positive and complementary role in guiding noisy image segmentation.The improved algorithm cab be successfully used for different noisy image segmentation,and segmentation results show that the mean squared error of image pixels are greatly reduced. |
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| Keywords: | image segmentation fuzzy C-means clustering local spatial information non-local spatial information |
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