摘要
针对数字图像中常见的混合噪声以及边缘轮廓模糊的问题,提出一种修正的阿尔法均值滤波与边缘增强算法相结合的图像预处理算法。修正的阿尔法均值滤波算法首先对像素矩阵中的像素值统计排序,其次去除定量的最大值和最小值,再次求取像素矩阵中剩余像素点的均值,最后用求取的均值代替原始中心点的像素值从而实现图像去噪。边缘增强算法首先使用Sobel算子定位图像边缘信息,提取图像的边缘后,将边缘叠加于去噪图像,最终实现图像的边缘复合增强。经验证,随着噪声密度的不断增加,该算法相比于传统算法始终保持着较小的均方误差值,且均方误差的增长率约为31%。结果表明,该算法有效滤除了数字图像的混合噪声,增强了边缘信息,同时满足图像降噪系统的实时性要求。
Aiming at the common problems of mixed noise and fuzzy edge contour in digital images,an image preprocessing algorithm combining modified alpha mean filtering and edge enhancement algorithm is proposed.The modified alpha mean filter algorithm first statistically sorts the pixel values in the pixel matrix,then removes the quantitative maximum and minimum values,and then calculates the average value of the remaining pixels in the pixel matrix.Finally,the average value obtained is used to replace the pixel value of the original center point to achieve image denoising.The edge enhancement algorithm first uses the Sobel operator to locate the edge information of the image,and after extracting the edge of the image,the edge is superimposed on the denoised image,and finally the edge composite enhancement of the image is realized.It has been verified that with the continuous increase of noise density,the algorithm has always maintained a smaller mean square error value than traditional algorithms,and the mean square error growth rate is about 31%.The results show that the proposed algorithm effectively filters out the mixed noise of digital images,enhances the edge information,and satisfies the real-time requirements of the image noise reduction system.
作者
陈伟
党榕
Chen Wei;Dang Rong(College of Communication and Information Engineering,Xi′an University of Science and Technology,Xi'an 710600,China)
出处
《电子测量技术》
北大核心
2021年第16期135-140,共6页
Electronic Measurement Technology
作者简介
陈伟,博士,副教授,主要研究方向为光电信息处理。E-mail:zebeck@111.com;党榕,硕士研究生,主要研究方向为数字图像处理。E-mail:19207205065@stu.xust.edu.cn。
