北京航空航天大学学报 ›› 2009, Vol. 35 ›› Issue (7): 833-837.

• 论文 • 上一篇    下一篇

基于改进NL-means算法的显微CT图像降噪

李保磊, 杨 民, 李俊江   

  1. 北京航空航天大学 机械工程及自动化学院, 北京 100191
  • 收稿日期:2008-06-18 出版日期:2009-07-31 发布日期:2010-09-16
  • 作者简介:李保磊(1980-), 男, 山东菏泽人,博士生, baolei_li@yahoo.com.cn.

Denoising of micro-CT image based on improved NL-means algorithm

Li Baolei, Yang Min, Li Junjiang   

  1. School of Mechanical Engineering and Automation, Beijing University of Aeronautics and Astronautics, Beijing 100191, China
  • Received:2008-06-18 Online:2009-07-31 Published:2010-09-16

摘要: 显微CT(Computed Tomography)采用微焦点射线源,射线剂量低,CT图像噪声大,对其降噪十分必要.综述了现存主要CT图像降噪算法及其优缺点,介绍了NL(nonlocal)-means算法,根据实验结果分析了其会在图像平滑区域引入人工伪影的不足.根据NL-means算法的不足,在原算法中引入图像的梯度信息,提出了改进的降噪算法,改进算法保持了原算法优良的降噪功能,并能有效抑制人工伪影,且能够提高图像细节对比度,实验结果验证了改进算法的有效性.

Abstract: Micro-CT(computed tomography)is based on microfocus X-ray source and the ray dose is low. So the noise level of micro-CT image is big and denoising of the CT image is very necessary. The current main denoising methods for CT image and their advantages and disadvantages were summaried. The NL(nonlocal)-means algorithm was described. According to the experiment result, the disadvantage of NL-meas algorithm that artificial artifact will be introduced in smooth region of CT image was analyzed. Based on the shortage of the NL-means algorithm, gradient information of image was introduced in the original algorithm and the improved algorithm was put forward. The improved algorithm keeps the excellent denioising function and the artificial artifact was restrained effectively. The detail contrast can be also enhanced. The availability of the improved algorithm was validated by the experiment result.

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