基于改进的各向异性模型对IVUS图像降噪算法
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北京工业大学电子信息与控制工程学院 北京 100124

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TP317.4

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IVUS image denoising algorithm based on improved anisotropic model
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College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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    摘要:

    针对血管内超声图像中的强背景噪声和边缘模糊等问题,提出了一种改进的各项异性扩散滤波算法。引入中值滤波,将滤波后的梯度模代替传统各向异性滤波中原始图像的梯度模,以控制扩散的过程,并能较好地保持边缘的特性;将各向异性扩散方程的常规扩散方向由4个方向扩展为8个方向,可保留更多的图像细节;并提出了一种自适应选取扩散门限的方法,解决了滤波和边缘保持的矛盾。实验结果表明,改进的算法在滤除噪声和保留边缘方面有着比较满意的效果,为以后血管内超声图像中外膜的提取提供了基础。

    Abstract:

    According to the problem of the strong background noise and edge blur in intravascular ultrasound(IVUS) images, an improved anisotropic diffusion is proposed. Firstly, median filter is imported to the PM algorithm, and then the gradient mode of the original image is replaced with the gradient mode from the image which is smoothed by the median filter to control the process of diffusion. Secondly, the direction of the conventional diffusion anisotropic diffusion equation is extended from 4 directions into 8 directions to retain more image details. Thirdly, a method of adaptive selection of the diffusion threshold K is put forward. The experimental results show that the improved algorithm has a satisfactory effect in removing noise and preserving edge, and providing a basis for the edge extraction of intravascular ultrasound images.

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王雨婷,汪友生.基于改进的各向异性模型对IVUS图像降噪算法[J].电子测量技术,2017,40(10):148-152

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  • 在线发布日期: 2017-12-05
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