Nonlocal Means-Based Speckle Filtering for Ultrasound Images
Nonlocal Means-Based Speckle Filtering for Ultrasound Images
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DOI：
10.1109/tip.2009.2024064
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发表时间：
2009-10-01
影响因子：
10.6
通讯作者：
Barillot, Christian
中科院分区：
文献类型：
--
作者：
Coupe, Pierrick;Hellier, Pierre;Barillot, Christian
在图像处理中，复原被期望改善图像的定性检测和定量图像分析技术的性能。本文提出了一种自适应的非局部（NL）均值滤波器，用于超声（US）图像中的斑点噪声抑制。最初开发的加性白色高斯噪声，我们建议使用贝叶斯框架，以获得一个NL-均值滤波器适用于相关的超声噪声模型。合成数据的定量结果显示所提出的方法相比，完善的和国家的最先进的方法的性能。在真实的图像上的实验结果表明，该方法能够准确地保持图像的边缘和结构细节。
In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the nonlocal (NL)-means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image.