基于相邻像素平均的超声图像散斑降噪

Zahra Hosseini, Mohammadreza Hassannejad Bibalan
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引用次数: 3

摘要

本文提出了一种去除超声图像中散斑噪声的新方法。超声成像系统的主要问题是存在散斑噪声,散斑噪声会导致图像边缘和细节的退化。在该方案中,提出的抑制散斑噪声的方法是邻域像素平均(NPA)滤波器,它基于窗口像素均值的邻域内的唯一像素进行平均。所提出的邻近标准是基于一个由像素的标准偏差(STD)决定的因素。它在自己的窗口中对相邻像素使用统一的加权因子,并用这个新值替换中心像素。通过实验仿真验证了NPA滤波器与其他类型去斑滤波器的性能。应用多幅医学超声图像,结果表明该方法具有较好的散斑降噪效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speckle Noise Reduction Of Ultrasound Images Based On Neighbor Pixels Averaging
In this paper, a novel approach for removing the speckle noise in ultrasound images has been proposed. The main problem of ultrasound imaging systems is the presence of speckle noise, which causes the edges and fine details degradation. In this scheme, the proposed method to suppress the speckle noise is neighbor pixels averaging (NPA) filter, which averages based on the only pixels which are in a neighborhood of the window’s pixels mean. The proposed criterion for vicinity is based on a factor determined by the standard deviation (STD) of pixels. It utilizes a uniform weighting factor for neighbor pixels in its own window and replaces the center pixel with this new value. The performance of NPA filter in comparison with other types of despeckling filters through experimental simulations is verified. Several medical ultrasound images were employed and the obtained results clearly show the better performance of proposed approach in speckle noise reduction.
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