基于数学形态学FCM聚类原型图像降噪方法

由传感器得到的图像往往含有大量噪声,针对目前常用的二维直方图算法在图像噪声检测与分离过程中存在的不足,以及传统FCM聚类算法的特点,提出了一种基于数学形态学的FCM聚类原型初始化方法:首先基于数学形态学理论确定图像初始聚类点簇,然后运用FCM对点簇进行处理。理论分析与实验表明,该方法能有效消除图像中的噪声点,对均匀噪声背景下图像处理有一定的应用价值。

The Image Noise Reduction Method Based on FCM Clustering Prototype with Mathematical Morphology

The images from sensors often contain a lot of noise. Aiming at the limitations of two-dimensional histogram algorithm which commonly used in image noise detecting and separating as well as the features of traditional FCM clustering algorithm, a method of FCM clustering prototype initialization based on mathematical morphology is presented: firstly, the image initial clustering cluster is determined based on the theory of mathematical morphology, and then the cluster is processed through the algorithm of FCM. Theoretical analysis and experiment show that the approach can effectively eliminate the image noise and has certain application value for processing the images with uniform noise background.