结合峰值检测的高噪声图像快速聚类分割方法
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国家部委资助项目(51329060101)


Fast Clustering Segmentation Method Combining Peak Testing forImage with High Noise
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    摘要:

    针对高噪声污染图像,提出一种结合峰值检测算法的快速聚类分割方法(FC-ImSeg)。根据平行线投影分割算法将二维直方图映射到一维空间,利用峰值检测算法检测图像像素点的聚类结果,调整映射模型的平行线宽度,使直方图符合双峰分布特性,最后利用加权模糊c均值聚类算法实现图像的分割。实验结果证明了该方法是快速有效的。

    Abstract:

    Aiming at image with high noise, a fast clustering segmentation approach combining peak testing is proposed in this paper. Two-dimension histogram was converted into one-dimension with parallel projection segmentation algorithm. Peak testing algorithm was used to test the clustering result of the pixels in noisy image. Parallel width in projection model was adjusted according to the testing result. As the histogram is approximated by double-peak distribution, noisy image can be segmented with weighted Fuzzy c-Means clustering algorithm. Experimental results proved that the proposed approach is fast and effective.

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赵晖,林成龙,唐朝京.结合峰值检测的高噪声图像快速聚类分割方法[J].国防科技大学学报,2010,32(2):51-55.
ZHAO Hui, LIN Chenglong, TANG Chaojing. Fast Clustering Segmentation Method Combining Peak Testing forImage with High Noise[J]. Journal of National University of Defense Technology,2010,32(2):51-55.

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  • 收稿日期:2009-09-09
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  • 在线发布日期: 2012-09-19
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