摘要
针对当前算法在抑制医学影像图像的噪声、精准地确定阈值方面不太理想,本文研究了小波分析算法的数学模型,利用仿真软件对小波分析除噪算法的实现进行了设计研究,探讨了合适的除噪方法。进一步对小波阈值不同门限降噪方法的处理结果进行了仿真比较研究,表明利用小波分析的医学影像图像除噪效果较好,便于实现。
Aiming at the fact that the current algorithm is not ideal in suppressing noise of medical image and accurately determining the threshold,this paper studies the mathematical model of wavelet analysis algorithm,the design research is realized,and the appropriate method of noise cancellation for wavelet analysis of noise cancellation algorithm was discussed by using the simulation software.Further for different threshold wavelet threshold de-noising methods,simulations on the processing results were carried out and comparative studies were conducted.The results show that the denoising effect of medical image using wavelet analysis is good and easy to implement.
作者
陈军
CHEN Jun(Department of Medicine,Dingxi Campus,Gansu University of Chinese Medicine,Dingxi 743000,China)
出处
《贵州大学学报(自然科学版)》
2020年第5期78-81,88,共5页
Journal of Guizhou University:Natural Sciences
基金
甘肃省高等学校科研资助项目(2018A-176)
甘肃中医药大学定西校区科研资助项目(2019XJYB01)。
关键词
小波分析
医学影像图像
小波阈值
除噪
wavelet analysis
medical images
wavele threshold
denoise