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基于模糊加权熵的医学图像多阈值分割
Fuzzy Weighted Entropy for Multi-Level Threshold Medical Image Segmentation
【摘要】 针对H.D.Cheng等人提出的模糊熵公式存在不满足区域一致性条件等问题,提出了模糊加权熵公式,证明了该公式满足图像分割定义的五个条件,克服了传统方法导致图像细节被均衡的不足,可得到较佳的分割结果。另外,隶属函数采用一种梯形分布,该分布可降低了参数的维数,提高了运算的效率。
【Abstract】 H.D.Cheng introduced fuzziness into maximum entropy approach and proposed the fuzzy c partitions maximum entropy. But it was not satisfied the definition of image segmentation, a fuzzy weighted entropy is proposed to solve the disadvantage. In addition, membership function is a trapezia distribution which can reduce the parameter’ s dimension and shorten the computational time.
【关键词】 图像分割;
阈值;
模糊熵;
隶属函数;
【Key words】 Image Segmentation; Threshold; Fuzzy Entropy; Membership Function;
【Key words】 Image Segmentation; Threshold; Fuzzy Entropy; Membership Function;
【基金】 国家自然科学基金资助项目(60572112)
- 【文献出处】 微计算机信息 , 编辑部邮箱 ,2006年36期
- 【分类号】TP391.41
- 【被引频次】5
- 【下载频次】242