计算机科学 ›› 2020, Vol. 47 ›› Issue (6): 170-175.doi: 10.11896/jsjkx.190400052
刘淑君, 魏莱
LIU Shu-jun, WEI Lai
摘要： 基于谱聚类的子空间聚类算法已经显示出良好的效果,但是传统的子空间聚类算法需要将图像进行向量化处理,而这种向量化会导致图像本身携带的二维结构信息的丢失。为了减少这种信息的丢失,文中提出了基于分块集成的图像聚类算法(Block Integration Based Image Clustering,BI-CI)。首先,将图像数据分为若干矩阵块;然后,利用核范数矩阵回归构造基于某一矩阵块的系数矩阵,同时提出了一种依据矩阵块秩信息设定各个矩阵块的权重方法;最后,通过每一系数矩阵及其所对应矩阵块的权重,得到整体系数矩阵。在此系数矩阵上,利用谱聚类算法得到最终的聚类结果。在4个图像数据集上的实验表明,相比现有算法,所提算法具有更强的鲁棒性,可以获得更优的聚类效果。
中图分类号:
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