资料下载
×
基于医学图像的有效中值滤波算法研究
消耗积分:2 |
格式:rar |
大小:260 |
2009-08-13
吴湛
分享资料个
本文对于由Visible Human 所提供的人体CT 图像序列所形成的体数据场，提出了一种有效的快速中值滤波方法。中值滤波是一种非常有用的非线性滤波技术，能有效的抑制脉冲噪声、椒盐噪声等。针对于医学CT 图像中要滤除的噪声干扰，本文提出了一种有效的快速中值滤波方法。为了克服中值滤波的模糊边缘特征的缺点，先人工干预在边缘附近设置一阈值，构造一中间矩阵M，利用窗口内数据间的相关性，设计了快速的移动剔除过程，并在原排序基础上进行快速比较排序，缩减排序过程和次数，加快了滤波速度，一定程度地避免了边缘的模糊。
关键词: 体数据；医学图像；中值滤波；边缘增强
Abstract：Based on the medical slice images data set formed from Visible Human, this paper puts forward an effective and accelerated median filtering method. Median filtering is a useful nonlinear filtering technology. It can remove pulse noise and jiaoyan noise effectively. Aiming at the noises in the medical CT slice images, we put forward this effective and accelerated median filtering method in this paper. In order to overcome the disadvantage that median filtering always blurs the fringe characters of images, a threshold value is set firstly
around the edge, and thereby a midway matrix M is constructed. Meanwhile, using the pertinence of these data in this window, an accelerated eliminating and arraying process are designed. By this means, we successfully reduce the course and number of arraying and speedup the filtering and avoid blurring the edge information.
Key words: data set; medical images; median filtering; edge restoration
关键词: 体数据；医学图像；中值滤波；边缘增强
Abstract：Based on the medical slice images data set formed from Visible Human, this paper puts forward an effective and accelerated median filtering method. Median filtering is a useful nonlinear filtering technology. It can remove pulse noise and jiaoyan noise effectively. Aiming at the noises in the medical CT slice images, we put forward this effective and accelerated median filtering method in this paper. In order to overcome the disadvantage that median filtering always blurs the fringe characters of images, a threshold value is set firstly
around the edge, and thereby a midway matrix M is constructed. Meanwhile, using the pertinence of these data in this window, an accelerated eliminating and arraying process are designed. By this means, we successfully reduce the course and number of arraying and speedup the filtering and avoid blurring the edge information.
Key words: data set; medical images; median filtering; edge restoration
声明：本文内容及配图由入驻作者撰写或者入驻合作网站授权转载。文章观点仅代表作者本人，不代表电子发烧友网立场。文章及其配图仅供工程师学习之用，如有内容侵权或者其他违规问题，请联系本站处理。 举报投诉
评论(0)
发评论
- 相关下载
- 相关文章
