一种引入ISODATA动态聚类的医学图像中值滤波算法

目的；提出一种医学图像中值滤波算法，以改进经典中值滤波存在的不足。方法：将模式 识别中的ISODATA聚类引入到中值滤波算法中，将分类的结果作为参数来确定如何进行中值滤波，以及是否需要进行中值滤波处理。结果：本算法能够滤除严重的脉冲噪声干扰，同时保持图像细节。结论：本算法跟经典中值滤波算法相比，提高了信噪比，增强了图像质量。

A median filter algorithm importing ISODATA dynamic clustering for medical imaging.

To improve conventional median filter algorithm employed in medical imaging, we proposed a new median filter algorithm importing ISODATA dynamic clustering for pattern recognition. The result of clustering was set as the parameters to decide if median filter was necessary and when it was, how the process was to be carried out. As shown in our test, this algorithm was capable of eliminating serious impulse noises and retain thorough image details, therefore enhanced signal to noise ratio and quality of the images in contrast with the conventional median filter algorithm.