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Speckle noise reduction in ultrasound images using fuzzy logic based on histogram and directional differences

机译:基于直方图和方向差的模糊逻辑减少超声图像中的斑点噪声

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Ultrasound imaging has been considered as the most powerful techniques for imaging organs and soft tissue structures in the human body. However its main limitation is its poor quality of images which are degraded by speckle noise. Speckle is a multiplicative form of noise which is inherent in ultrasound imaging but carries some useful information which should be filtered out without losing the features in an image. Fuzzy logic has the capability of handling the input that is approximate rather than fixed and exact. Since the ultrasound images have fuzziness in nature caused by speckle noise, vague edges and boundaries, fuzzy logic can be considered as the simple way to arrive at a definite output based on vague, ambiguous, imprecise or noisy input information. In this paper, a novel fuzzy applied filter has been designed for speckle noise reduction based on directional differences in which noise affected pixels are classified depending on the magnitude of noise. Appropriate filters are applied on the corrupted pixels which gives appreciable improvement both visually and in PSNR values.
机译:超声成像被认为是对人体器官和软组织结构进行成像的最强大技术。然而,它的主要局限性在于其图像质量差,该图像质量会由于斑点噪声而降低。斑点是噪声的乘法形式,是超声成像中固有的噪声,但会携带一些有用的信息,这些信息应被滤除而不会丢失图像中的特征。模糊逻辑具有处理近似而不是固定和精确输入的能力。由于超声图像本质上是由斑点噪声,模糊的边缘和边界引起的模糊性,因此模糊逻辑可以被认为是基于模糊,模棱两可,不精确或嘈杂的输入信息来获得确定输出的简单方法。在本文中,基于方向差设计了一种新颖的模糊应用滤波器,用于减少斑点噪声,在该方向差中,受噪声影响的像素根据噪声的大小进行分类。在损坏的像素上应用适当的滤镜,可以在视觉上和PSNR值上带来明显的改善。

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