基于阈值邻域均值的医学超声图像去噪算法  

Denoising Algorithm for Medical Ultrasound Image with Threshold Neighborhood Average

作　　者：牟希农 MOU Xinong(Department of Medical Education,Dingxi Campus,Gansu University of Chinese Medicine,Dingxi 743000,China)

机构地区：[1]甘肃中医药大学定西校区医学教学部,甘肃定西743000

出　　处：《贵州大学学报（自然科学版）》2023年第1期75-78,共4页Journal of Guizhou University:Natural Sciences

基　　金：甘肃省高等学校创新能力提升项目(2020A-193)。

摘　　要：针对含有高密度椒盐和高斯噪声的医学超声图像去噪中细节信息保留不够,图像较模糊问题,提出了一种阈值邻域均值算法。该方法首先通过阈值策略法对指定邻域内像素加权均值与其中任一像素灰度值大小进行比较判断,然后将大于阈值的像素剔除,而小的作为有用信息输出,最后运用该方法对含有高密度椒盐和高斯噪声的医学影像图像进行去噪实现设计。仿真实验表明,阈值邻域均值算法对胰腺超声图像的高密度椒盐和高斯噪声抑制力强,计算速度快,峰值信噪比大于单纯的中值和均值算法,去噪后的图像质量更佳。To solve the problem of medical ultrasound image with high-density pepper and salt, and Gaussian noise, poor definition, and inadequate details, an threshold neighborhood average algorithm is proposed. The method first compares the weighted mean of designated pixel with any pixel gray value by threshold strategy, and then removes the pixels larger than the threshold, takes the smaller pixels as useful output information, and finally designs the denoising of the medical image with high-density salt and pepper noise, and Gaussian noise. Simulation experiments show that the threshold neighborhood average algorithm has strong high-density pepper and salt noise, and Gaussian noise suppression on pancreatic ultrasound image, fast computation, lager PSNR than pure median and mean algorithm, and better quality image after denoising.

关 键 词：医学超声图像 阈值邻域均值 去噪算法 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术] R445.9[自动化与计算机技术—计算机科学与技术]