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dc.contributor.author陈冠楠
dc.contributor.author潘建基
dc.contributor.author林居强
dc.contributor.author王廷银
dc.contributor.author陈荣
dc.contributor.author陈顺凡
dc.contributor.author洪亲
dc.contributor.author滕忠坚
dc.date.accessioned2016-05-17T02:50:58Z
dc.date.available2016-05-17T02:50:58Z
dc.date.issued2009
dc.identifier.citation激光生物学报,2009,(5):118-120+141
dc.identifier.issn1007-7146
dc.identifier.otherJGSW200905027
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/106183
dc.description.abstract基于偏微分方程的医学图像去噪方法已公认为具有显著效果的去噪技术。常用的偏微分方程去噪方法虽然可以去除变化平缓的图像中的噪声,同时保持边缘结构信息,但对带有较多纹理细节的医学图像的去噪效果却不太理想。在对目前有关纹理医学图像理解和综合的基础上,介绍了三种纹理图像去噪技术。第一种自适应调整参数的全变分方法,在不同尺度空间下去噪,可保持纹理和细节;第二种将医学图像空间由bV空间上升到g空间以保持纹理;第三种使用多尺度分解噪声以保持细节特征。这些方法均能在实际应用中达到一定的效果,但是如何更好的去除噪声,文章对其进行分析,并提出新的改进思路。
dc.description.abstractBiomedical images denosing based on partial differential equation are well-known for their good processing results.General denoising methods based on PDE can remove the noise of images with gentle change and preserve more structure detail of edges,but have a poor effectiveness on the denoising of biomedical images with many texture details.This paper attempts to make an overview of biomedical images texture detail denosing based on PDE.Three kinds of important image denosing schemes are introduced in this paper:one is image denosing based on the adaptive parameter estimation total variation model,which denosing the images based on muti-scale space;the other is using G norm to the perception of scale,which provides a more intuitive understanding of this norm;finial is multi-scale denosing decomposi- tion.These former can preserve more structure of biomedical images texture detail.Then this paper demonstrates the applications of the three kinds of methods.At the end,the future trend of biomedical images texture detail denosing based on PDE is pointed out.
dc.description.sponsorship国家自然科学基金项目(60778046);福建省科技项目(2008I0015;2008J0016);卫生部科研基金项目(WKJ2008-2-046)
dc.language.isozh_CN
dc.subject偏微分方程
dc.subject医学图像去噪
dc.subject纹理细节保持
dc.subject自适应调整
dc.subjectG空间
dc.subjectpartial differential equation
dc.subjectbiomedicine image denoising
dc.subjecttexture and detail preservation
dc.subjectadaptive parameter estimation
dc.subjectG norm
dc.title基于偏微分方程的保持纹理细节的医学图像去噪方法
dc.title.alternativeBiomedical Images Denosing with Texture and Detail Preservation Based on PDE
dc.typeArticle


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