基于空间模糊聚类的图像分割优化算法

Spatial Fuzzy Clustering Optimization Algorithm for Image Segmentation

针对传统模糊C-均值(FCM)算法抗噪性能差的问题,提出一种新的基于空间模糊聚类的图像分割优化算法.该算法通过在传统FCM算法基础上加入图像特征项中像素间的空间位置信息,解决了传统FCM对噪声敏感的问题,增强了算法的鲁棒性.实验结果表明,对于添加5%Gauss噪声的图像,该算法可实现有效分割,分割效果显著优于传统FCM算法.

For the poor anti-noise performance limitations of the traditional fuzzy C-means（FCM） algorithm,we proposed a new spatial fuzzy clustering optimization algorithm for image segmentation. We added a wealth of spatial information between pixels in the image feature items,so that the traditional FCM sensitive to noise was solved,and the robustness of the algorithm was enhanced. Experimental results show that our algorithm can achieve the effective segmentation of the 5% Gaussian noise images,and the results are significantly better than those by traditional FCM image segmentation algorithm.