摘要
数学形态学滤波属于非线性滤波,针对传统的线性滤波对图像边缘等细节特征容易模糊的缺点,本文提出一种基于灰度形态学的自适应加权复合滤波优化算法,采用凸性多尺度结构元素对灰度图像进行多级形态开闭运算,根据形态滤波等幂特性,实现结构元素序列的自适应加权复合滤波,并对滤波效果进行PSNR评价,实验仿真结果表明该复合滤波算法在保留图像细节特征的同时能有效去除噪声,提高了图像信噪比.
Mathematical morphology filter is a nonlinear filter. In viewing of the disadvantages for the traditional linear filtering is easy to blur the image edges,this paper presents an adaptive weighted composite filter optimization algorithm based on grayscale morphology. Base on the characteristic of nonlinear filtering,under the effect of convex multi-scale structural elements,this algorithm performs multistage morphological open-closed operation on grayscale image,and implements adaptive weighted composite filtering,and evaluates the effect of composite filtering by PSNR. The simulation results show that this adaptive weighted composite filtering algorithm can not only effectively remove noises but also preserve grayscale image details,and the PSNR values get improved.
作者
文永革
WEN Yongge(School of Information Engineering, Mianyang Teachers' College, Mianyang, Sichuan 621000)
出处
《绵阳师范学院学报》
2018年第5期81-86,共6页
Journal of Mianyang Teachers' College
基金
四川省教育厅科研项目"虚拟现实系统中关键技术研究"(13ZA0114)
绵阳师范学院教改项目"MATLAB在<数字图像处理>教学中的仿真应用"(Mnu-JY16174)资助
关键词
灰度形态学
自适应权值
滤波算法
图像仿真
grayscale morphology
adaptive weight
filtering algorithm
image simulation