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基于谱聚类的图像多尺度随机树分割 被引量：14

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摘要 针对谱聚类(spectral clustering)应用于图像分割时权矩阵的谱难以计算的实际问题,定义了像素点与类之间的距离,给出一个采样数定理,设计了一个图像的分层分割(hierarchical divisive)算法.在利用该算法进行图像分割时,由于既要对待分类的点进行随机抽样,又要通过调节尺度因子来合并较小的类或拆分较大的类,因此图像的分割既具有随机性又具有多尺度特性,称之为基于谱聚类的图像多尺度随机树分割(multiscale stochastic hierarchical image segmentation by spectral clustering,简写为MSHISSC).实验结果表明了算法的有效性.
作者 李小斌 田铮
机构地区 西北工业大学应用数学系 中国科学院自动化研究所模式识别国家重点实验室
出处 《中国科学（E辑）》 CSCD 北大核心 2007年第8期1073-1085,共13页 Science in China(Series E)
基金 国家自然科学基金(批准号:60375003) 航空科学基金(批准号:03I53059)资助项目
关键词 谱聚类图 多尺度 随机树 图像分割
分类号 TN911.73 [电子电信—通信与信息系统]
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参考文献15

  • 1Kanungo T, Mount D M, Netanyahu N S, et al. An efficient k-means clustering algorithm: Analysis and implementation. IEEE Trans Pattern Anal Mach Intell, 2002, 24(7): 881-892
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二级参考文献16

  • 1Bach R, Jordan M I. Learning spectral clustering. University of California at Berkeley Technical report UCB/CSD-03-1249.2003
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  • 7Shi J, Malik J. Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell, 2000, 22(8): 888-905
  • 8Fowlkes C, Belongie S, Chung F, et al. Spectral grouping using the Nystrom method. IEEE Trans Pattern Anal Mach Intell,2004, 26(2): 214-225
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共引文献32

同被引文献224

引证文献14

二级引证文献51

中国科学（E辑）
2007年 第8期

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