基于边缘扩散的医学图像非线性去噪算法*

在对医学图像去噪的同时保留边缘信息，对于后期的诊断具有重要的意义。分析了ＰＭ和Ｃａｔｔｅ算法 以及它们的不足，提出了一种基于边缘扩散的非线性去噪方法，通过边缘检测把图像分为边缘和非边缘两部分， 非边缘区域通过各向同性算法去噪；边缘区域通过各向异性算法去噪，改进扩散形式，只沿边缘方向扩散去噪。 实验表明方法非常有效，带噪声的医学图像经过改进后的算法去噪处理，图像质量得到明显的改善。

Nonlinear algorithm based on edge diffusion for medical image denoising

It is necessary to keep the edge details while removing the noise of the medical image, for the purpose of the further diagnosis. This paper proposed a nonlinear denoising algorithm based on edge diffusion according to the disadvantages of the PM algorithm and divided the Catte algorithm. Image into the edge and the no-edge through the edge detection algorithm, the edge area denoised by the isotropic algorithm, the no-edge area denoised by the anisotropic diffusion algorithm, improve the form of diffusion, only along edge direction. Experiments show that the proposed method is very effective, with the noise of medical image denoising through the improved algorithm, image quality got obvious improvement.