基于边缘估计的自适应各向异性扩散的医学超声图像降噪算法

Adaptive Anisotropic Diffusion Medical Ultrasound Image Denoising Method Based on Edge Estimate

提出了一种针对医学超声图像的自适应各向异性扩散算法;该算法充分利用图像本身的边缘信息以及图像水平和垂直方向梯度的差异,用GHAD方法在两个方向设置不同的梯度门限,避免了传统的常数及单一梯度门限带来的鲁棒性差等问题;改进的扩散系数改善了传统扩散系数收敛过快及边界平滑的问题;经过多组仿真实验,综合峰值信噪比(PSNR)和边缘保持度(FOM)等指标,表明该算法相比同类算法有更好的降噪和边缘保持效果。

An adaptive anisotropic diffusion algorithm based on edge estimate is proposed for medical ultrasound image.The algorithm makes full use of edge information and gradient difference in the horizontal and vertical directions,uses GHAD method to set gradient threshold for two directions,overcomes the poor robustness of traditional gradient threshold.The improved diffusion coefficient ameliorates traditional coefficient＇s shortcomings of convergence and edge smoothing.Compared with other similar methods,experiments show that the proposed algorithm has better performance for noise removal（PSNR）and edge-preservation（FOM）.