基于中性粒细胞的医学超声图像去斑非局部均值滤波器

Niloofar Rahimizadeh, Reza P. R. Hasanzadeh, M. Ghahramani, F. Janabi-Sharifi
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引用次数: 4

摘要

为了提高非局部均值(NLM)滤波器处理超声图像散斑噪声的性能,提出了一种新的基于嗜中性逻辑的权函数。在嗜中性域,每个像素由真值隶属度T、不确定性隶属度I和假值隶属度f三个分量来表征。在我们提出的方法中,根据US图像中噪声的性质,引入修正函数来获取嗜中性分量。然后,我们利用这些分量来度量像素之间的相似度,并设计合适的权函数来提高NLM滤波器的去斑性能。通过对美国的综合和真实数据的评价,表明了我们提出的方法与其他先进技术相比的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Neutrosophic based Non-Local Means Filter for Despeckling of Medical Ultrasound Images
In this paper, a new weight function based on neutrosophic logic is presented for improving the performance of non-local means (NLM) filter to deal with speckle noise in ultrasound (US) images. In neutrosophic domain, each pixel is characterized by three components including truth membership T, indeterminacy membership I and falsity membership F. In our proposed method, according to the nature of noise in US images, modified functions are introduced for obtaining neutrosophic components. Then, we apply these components for measuring the similarity between pixels and designing a proper weight function to improve despeckling performance of NLM filter. The evaluations on synthetic and real US data show superiority of our proposed method compared to other state-of-the-art techniques.
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