一种加权中值滤波算法在医学磁共振图像去噪中的应用

为了更好地去除医学磁共振图像(MRI)中的高密度椒盐噪声和高斯噪声,提出了一种加权中值滤波算法.该算法的核心思想是利用改良的有限阈值策略对滤波窗口的每个像素点的灰度值与计算该像素点所得的相应权值之积进行求和,然后将运算结果作为滤波窗口中心点的输出值.利用该算法对含有高密度椒盐噪声和高斯噪声的医学MRI进行去噪仿真实验表明,该算法对高密度椒盐噪声和高斯噪声的抑制力显著优于单纯的中值算法和均值算法,且去噪后的图像具有良好的细节保真度和清晰度.

Application of weighted median filtering algorithm in denoise of magnetic resonance imaging

In order to better remove high - density salt and pepper noise, and Gaussian noise in medical magnetic resonance images(MRI), a weighted median filtering algorithm is proposed.The main idea of the method is to weight the gray scale value of each pixel in the filtered window against the corresponding weights product computed at the pixel point by using a modified finite threshold strategy, and then takes the operation result as the output value of the central point of the filter window. Medical MRI containing high - density salt and pepper noise, and Gaussian noise was noise - removed using a weighted median filtering algorithm.Simulation experiments show that proposed algorithm is highly stable, and the inhibitory force of both high - density pretzel noise and Gaussian noise in the medical MRI significantly outperforms the simple median and mean algorithm, and the denoised image has good detail fidelity and clarity.