图像分割的改进稀疏子空间聚类方法

提出一种基于改进稀疏子空间聚类的图像分割方法。首先将图像进行过分割得到一些均匀区域称为超像素,并提取超像素的颜色直方图作为其特征;然后建立特征数据的改进稀疏子空间表示并由此构造图相似度矩阵,最后利用谱聚类算法得到超像素的聚类结果并作为图像分割结果。实验结果表明,本文提出的改进稀疏子空间聚类方法具有良好的聚类性能,对噪声具有一定的鲁棒性;用于自然图像能够得到更好的分割效果。

Improved sparse subspace clustering method for image segmentation

A novel image segmentation method based on improved sparse subspace clustering is presented. The image to be segmented is over partitioned into some uniform sub regions called superpixels, and color histogram of each superpixel is computed as its feature data. Then by employing an improved sparse subspace representation model, the sparse representation coefficient matrix is computed and used to construct the affinity matrix of a graph. Finally, the spectral clustering algorithm is used to obtain the image segmentation result. Experiments show that the proposed improved sparse subspace clustering method performs well in clustering and is robust to noise. It can obtain good segmentation results for natural color images.