多邻域中值滤波算法在医学图像中的应用

The application of multi-neighborhood median filterin medical images

目的:克服现有的滤波算法在噪声检测与噪声滤除上的缺陷,进一步提高去噪性能.方法:提出了多邻域中值滤波算法,对噪声检测和噪声滤除的方法分别进行改进.算法用邻域中的灰度极值进行噪声检测,对检测出来的可疑噪声,用邻域的中值作进一步的噪声检测.对噪声像素,在其邻近的9个邻域中分别求出信号像素的中值,然后用所有中值的中值作为噪声像素新的灰度.结果:基于医学图像的实验结果证明,相对于现有的算法,所提出的算法的去噪图像更加清晰,去噪结果的PSNR和SSIM值更高.结论:所提出的算法在彻底去除噪声的同时,很好地保持了图像的纹理边缘和细节,相对于现有的滤波算法,具有更好的去噪性能.

Objective:To overcome the drawbacks of existing filters in noise detection and removal,and further improve the denoising performance.Methods:We propose a multi-neighborhood median filter to improve the techniques of noise detection and removal.This proposed filter first performs noise detection by the extreme intensity values of neighborhood,and then performs further noise detection by the median of neighborhood.For noisy pixel,it searches for the medians of nine neighboring neighborhood respectively,and then take the median of all medians as the new intensity of noisy pixel.Results:The experimental results with medical images,show that compared to the existing filters,the propose method obtains clearer denoised images,and achieves higher PSNR and SSIM values.Conclusion:The proposed method can preserve the edges and details of image very well,while removing the noises thoroughly;comparing to the existing filters,the proposed method shows better denoising performance.