摘要
针对传统医学图像增强效果不理想、边界模糊不清、不利于病情诊断等问题,提出了一种改进的医学图像增强算法。首先创建一个适合的隶属度函数实现图像由时域到变换域的变换,通过迭代方法加强变换域的细节成分,最后通过模糊逆变换得到增强后的时域图像。采用的适合隶属度函数,增强了图像效果,使图像细节更清晰。实验表明,采用模糊方法比传统的几种方法可以更有效抑制噪声,提取医学图像中的有用信息,更加有利于病情的诊断。
According to the shortcomings of traditional algorithm used to medical images,such as undesirable enhancement effect,unclear fuzzy boundary and disbenefit to diagnosis,an improved medical image fuzzy-enhancement algorithm is proposed. An appropriate subordinating degree function is created to achieve the image transform from time domain to transform domain. The nonlinear iterative method is used to enhance the detail composition in the transform domain. The enhanced time-domain image is obtained through the fuzzy inverse transform. The appropriate subordinating degree function can enhance image effect and make the image detail more clear. Experimental results show that the fuzzy enhancement method can suppress noise more ef-fectively,extract more useful information in medical images and is more beneficial to diagnosis in comparison with traditional methods.
出处
《现代电子技术》
2014年第12期67-69,共3页
Modern Electronics Technique
基金
国家自然科学基金资助项目(60802018)
广西壮族自治区教育厅项目(2012JGA240)
关键词
图像增强
模糊集
隶属度函数
模糊逆变换
image enhancement
fuzzy set
subordinating degree function
fuzzy inverse transform
