基于空间约束的模糊核聚类红外图像分割

Infrared Image Segmentation Based on Fuzzy Kernel Clustering Using Spatial Constrained

提出了一种基于空间约束的模糊核聚类红外图像分割算法。首先将图像映射到特征空间,在特征空间内进行模糊聚类,针对红外图像中存在的噪声点和野值等干扰问题引入了像素点的八邻域局部空间约束信息,并定义了像素分类可靠性指数修正隶属度函数在整个图像范围内分析像素分类的合理性,其中像素分类可靠性指数包括像素分类灰度可靠性指数和像素分类距离可靠性指数。实验结果表明,这种考虑局部空间约束和整体空间约束的模糊核聚类算法可更有效地对红外图像进行分割。

A method for infrared image segmentation based on fuzzy kernel clustering using spatial relation was proposed. Firstly,the image was mapped into feature space. The fuzzy clustering was performed in this space. In order to suppress the noise, the part spatial information was introduced. And the classification reliability of pixel which was im- proved the degree of membership function, was used to analysis the classification rationality in the whole image. The classification reliability of pixel gray and the classification reliability of pixel distance were included in the the classifi- cation reliability of pixel. The experimental results show the infrared image can be segment well by fuzzy kernek clustering using the part spatial information and the whole spatial information.