摘要
传统去噪方法在处理高强度噪声干扰图像时,往往不能有效去除噪声且在修复过程容易引入二次污染。为此,提出一种边缘图导向的非局部图像均值滤波算法。首先获取二阶差分边缘信息,在非局部范围内搜索相似块,以边缘导向图与噪声图像共同生成滤波器权值,进而构建由边缘信息导向的非局部协同滤波框架。与传统滤波为代表的局部线性滤波方法相比,所提出算法能挖掘图像边缘信息并利用一种新的非局部协同滤波框架进行图像去噪,因此增强了高强度噪声干扰环境下的边缘修复能力。实验证明,提出算法在高强度噪声污染的情况下,修复的图像不仅获得了更高的测量指标,视觉效果也更加理想。
When traditional denoising methods are used to deal with the image interfered by high intensity noise,the noise can not be removed effectively and secondary pollution is easily introduced in the repair process.In order to solve this problem,a kind of marginal figure oriented non-local means filtering algorithm is proposed.First of all,the second order difference edge information is obtained,and similar blocks within the scope of the non-local is searched. Then,the edge guided image and noise image are both used to generate filter weights,so that the edge information oriented non-local collaborative filtering framework is constructed. Compared with the local linear filtering method represented by the traditional filtering,the proposed algorithm can explore the edge information of the image and use a new non-local collaborative filtering framework for image denoising enhancing the edge repair ability under the environment of high intensity noise interference. Experimental results show that under the condition of high intensity noise pollution,the improved image gets higher measurement index,and has better visual effect.
作者
傅博
吴越楚
王丽妍
王瑞子
FU Bo;WU Yuechu;WANG Liyan;WANG Ruizi(College of Computer and Information Technology,Liaoning Normal University,Dalian 116081,China)
出处
《吉林大学学报（信息科学版）》
CAS
2020年第6期687-693,共7页
Journal of Jilin University（Information Science Edition）
基金
国家自然科学基金资助项目(61702246)
中国博士后基金资助项目(2019M651123)
大连市高层次人才创新支持计划(青年科技之星)基金资助项目(2018RQ65)。
关键词
边缘导向图
非局部均值
图像去噪
高强度噪声
edge guided image
non-local means
image denoising
high intensity noise
