Center for Biomedical Imaging and Bioinformatics, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
Magn Reson Imaging. 2010 Dec;28(10):1485-96. doi: 10.1016/j.mri.2010.06.023. Epub 2010 Sep 17.
The non-local means (NLM) filter removes noise by calculating the weighted average of the pixels in the global area and shows superiority over existing local filter methods that only consider local neighbor pixels. This filter has been successfully extended from 2D images to 3D images and has been applied to denoising 3D magnetic resonance (MR) images. In this article, a novel filter based on the NLM filter is proposed to improve the denoising effect. Considering the characteristics of Rician noise in the MR images, denoising by the NLM filter is first performed on the squared magnitude images. Then, unbiased correcting is carried out to eliminate the biased deviation. When performing the NLM filter, the weight is calculated based on the Gaussian-filtered image to reduce the disturbance of the noise. The performance of this filter is evaluated by carrying out a qualitative and quantitative comparison of this method with three other filters, namely, the original NLM filter, the unbiased NLM (UNLM) filter and the Rician NLM (RNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance over the other filters being compared.
非局部均值（NLM）滤波器通过计算全局区域中像素的加权平均值来去除噪声，并且优于仅考虑局部邻域像素的现有局部滤波器方法。该滤波器已成功从 2D 图像扩展到 3D 图像，并已应用于去除 3D 磁共振（MR）图像的噪声。本文提出了一种基于 NLM 滤波器的新滤波器，以提高去噪效果。考虑到 MR 图像中瑞利噪声的特点，首先对平方幅度图像进行 NLM 滤波去噪。然后进行无偏校正以消除有偏偏差。在执行 NLM 滤波器时，基于高斯滤波图像计算权重以减少噪声的干扰。通过将该方法与其他三种滤波器（即原始 NLM 滤波器、无偏 NLM（UNLM）滤波器和瑞利 NLM（RNLM）滤波器）进行定性和定量比较，评估了该滤波器的性能。实验结果表明，与其他比较的滤波器相比，所提出的滤波器在去噪性能方面取得了更好的效果。
