| 改进的模糊聚类遥感影像分割 |
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| 引用本文： | 高国勇.改进的模糊聚类遥感影像分割[J].测绘与空间地理信息,2015(6):98-100. |
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| 作者姓名： | 高国勇 |
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| 作者单位： | 辽宁省摄影测量与遥感院,辽宁沈阳,110034 |
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| 摘 要： | 聚类是数据挖掘的重要分支之一,引入模糊理论的模糊聚类分析为显示数据提供了模糊处理能力,在许多领域被广泛应用。本文应用考虑邻域关系的约束模糊C均值(Fuzzy C-Means with Constrains,FCM_S)算法,将邻域像素引入到目标函数中,进而有效地利用邻域像素信息,提高分割精度。本文应用FCM_S算法对模拟彩色纹理图像进行分割,计算其混淆矩阵,定性定量地与FCM算法进行对比分析,证明了该算法的鲁棒性。
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| 关 键 词： | 图像分割 聚类算法 邻域约束 模糊C均值聚类算法 |
Improved Fuzzy Clustering Image Segmentation Algorithm for Remote Sensing Images |
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| GAO Guo-yong.Improved Fuzzy Clustering Image Segmentation Algorithm for Remote Sensing Images[J].Geomatics & Spatial Information Technology,2015(6):98-100. |
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| Authors: | GAO Guo-yong |
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| Abstract: | Clustering is an important branch of data mining , fuzzy theory of fuzzy clustering analysis provides a fuzzy display data pro-cessing capability , is widely used in many fields .In the paper , considering constraints neighborhood relations Fuzzy C -means ( Fuzz-y C-means with Constrains , FCM_S) algorithm will be introduced to the neighboring pixels objective function , thus the effective use of field-pixel information to improve classification accuracy .In this paper , FCM_S algorithm to simulate color texture image classifi-cation, calculate the confusion matrix , qualitative and quantitative comparison with FCM algorithm analysis to prove the robustness of algorithm. |
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| Keywords: | image segmentation clustering neighborhood distance constraint fuzzy C-means clustering algorithm |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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