Vision Lab, Department of Physics, University of Antwerp, Belgium.
Phys Med Biol. 2010 Aug 21;55(16):N441-9. doi: 10.1088/0031-9155/55/16/N02. Epub 2010 Aug 3.
In this note, we address the estimation of the noise level in magnitude magnetic resonance (MR) images in the absence of background data. Most of the methods proposed earlier exploit the Rayleigh distributed background region in MR images to estimate the noise level. These methods, however, cannot be used for images where no background information is available. In this note, we propose two different approaches for noise level estimation in the absence of the image background. The first method is based on the local estimation of the noise variance using maximum likelihood estimation and the second method is based on the local estimation of the skewness of the magnitude data distribution. Experimental results on synthetic and real MR image datasets show that the proposed estimators accurately estimate the noise level in a magnitude MR image, even without background data.
在本注记中，我们将讨论在没有背景数据的情况下估算磁共振（MR）图像的幅度中的噪声水平。之前提出的大多数方法都利用 MR 图像中的瑞利分布背景区域来估计噪声水平。然而，这些方法不能用于没有背景信息的图像。在本注记中，我们提出了两种在没有图像背景的情况下估算噪声水平的不同方法。第一种方法基于使用最大似然估计的局部噪声方差估计，第二种方法基于幅度数据分布的偏度的局部估计。对合成和真实 MR 图像数据集的实验结果表明，即使没有背景数据，所提出的估计器也能准确地估算幅度 MR 图像中的噪声水平。
