改进型PM与递归滤波器相结合的图像去噪方法  

Image Denoizing Algorithm Based on Improved PM and Recursive Filter

作　　者：王凌志 周先春[1,2] 陈铭[1] WANG Lingzhi;ZHOU Xianchun;CHEN Ming(School of Electronic and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China;Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology,Nanjing University of Information Science and Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学电子与信息工程学院,江苏南京210044 [2]南京信息工程大学江苏省大气环境与装备技术协同创新中心,江苏南京210044

出　　处：《信息与控制》2019年第5期559-566,共8页Information and Control

基　　金：国家自然科学基金资助项目(11202106,61302188);江苏省“信息与通信工程”优势学科建设项目;江苏高校品牌专业建设工程资助项目

摘　　要：由于各向异性扩散算法在运用于图像去噪的过程中,容易产生图像边缘信息丢失,纹理细节模糊等现象.针对这一情况,提出了一种改进型PM与递归滤波器相结合的图像去噪算法,该算法首先通过控制梯度方向和垂直于梯度方向的扩散系数来保留图像的边缘信息,再通过递归滤波算法减少迭代次数来保护图像的细节纹理特征.实验结果表明,新方法在图像去噪和保护图像的边缘细节信息等方面都有着优越的效果,且大幅降低了均方差,对于图像的峰值信噪比也有显著的提高.In the image denoizing process, the anisotropic diffusion algorithm is prone to image edge information loss and texture detail blur. Considering this, an image denoizing algorithm combining improved PM and recursive filter is proposed. This algorithm first preserves the edge information of the image by controlling the coefficients of the diffusion in the gradient direction and that perpendicular to the gradient direction, and then the recursive filtering algorithm is used to reduce the number of iterations to protect the detailed texture features of the image. The experimental results show that the new method has superior effects in image denoizing and edge detail information protection, and greatly reduces the mean square error. The peak signal-to-noise ratio of the image is also significantly improved.

关 键 词：图像去噪 各向异性扩散 递归滤波器 梯度 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN911.7[自动化与计算机技术—计算机科学与技术]