关键词: 模糊C均值算法, 隐马尔可夫随机场, 核函数, 先验概率函数

Abstract: In view of fuzzy C-means algorithm is not considering the neighborhood information of the image, lead to the segmentation result is bad, combined with hidden Markov random field and Gaussian kernel function, put forward the nuclear space hidden Markov random field fuzzy C-means clustering algorithm. Introducte hidden Markov random field, introduce the spatial neighborhood information of pixels in the target function, the segmentation algorithm of noise robustness enhancement. The kernel function is introduced to map the nonlinear transform of the sample point to the high dimension feature space, which can enhance the anti jamming ability of the image segmentation, keep the image details. The standard image add noise to validate the performance of the improved algorithm. Both the visual effect and the peak signal to noise ratio of the segmented image show that the improved algorithm has better anti noise ability.

Key words: fuzzy C-means algorithm, hidden Markov random field, kernel function, prior probability function